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7
.githooks/pre-commit
Normal file
@@ -0,0 +1,7 @@
|
||||
#!/bin/sh
|
||||
|
||||
echo "Start pre-commit hook"
|
||||
|
||||
# Copy current state into sciebo on every commit
|
||||
# This excludes .directories and .files inside of bernstein_paper
|
||||
cp -r ./25_07_phd_defense/* ~/sciebo/PHD-Presentation-Backup
|
||||
7
.gitignore
vendored
@@ -60,12 +60,10 @@ data/*
|
||||
*.py.ipynb
|
||||
|
||||
# Potentially large but not binary
|
||||
*.svg
|
||||
# *.svg
|
||||
|
||||
# Binary files
|
||||
*.pdf
|
||||
*.jpg
|
||||
*.png
|
||||
*.zip
|
||||
*.gz
|
||||
*.tar
|
||||
@@ -85,4 +83,5 @@ data/*
|
||||
|
||||
# Ignore html files for now
|
||||
# TODO: Remove later
|
||||
*.html
|
||||
index_cache
|
||||
index_files
|
||||
|
||||
3
.gitmodules
vendored
@@ -1,3 +0,0 @@
|
||||
[submodule "02_crps_learning"]
|
||||
path = 02_crps_learning
|
||||
url = git@git.uni-due.de:dsee/papers/crps-learning-code.git
|
||||
8
.vscode/settings.json
vendored
Normal file
@@ -0,0 +1,8 @@
|
||||
{
|
||||
"files.autoSave": "off",
|
||||
"files.exclude": {
|
||||
"**/.git": false,
|
||||
".git": false
|
||||
},
|
||||
"todo-tree.tree.hideTreeWhenEmpty": false
|
||||
}
|
||||
@@ -1,31 +0,0 @@
|
||||
text_size <- 16
|
||||
width <- 12
|
||||
height <- 6
|
||||
|
||||
# col_lightgray <- "#e7e7e7"
|
||||
# col_blue <- "#F24159"
|
||||
# col_b_smooth <- "#F7CE14"
|
||||
# col_p_smooth <- "#58A64A"
|
||||
# col_pointwise <- "#772395"
|
||||
# col_b_constant <- "#BF236D"
|
||||
# col_p_constant <- "#F6912E"
|
||||
# col_optimum <- "#666666"
|
||||
|
||||
# https://www.schemecolor.com/retro-rainbow-pastels.php
|
||||
col_lightgray <- "#e7e7e7"
|
||||
col_blue <- "#F24159"
|
||||
col_b_smooth <- "#5391AE"
|
||||
col_p_smooth <- "#85B464"
|
||||
col_pointwise <- "#E2D269"
|
||||
col_b_constant <- "#7A4E8A"
|
||||
col_p_constant <- "#BC677B"
|
||||
col_optimum <- "#666666"
|
||||
col_auto <- "#EA915E"
|
||||
|
||||
T_selection <- c(32, 128, 512)
|
||||
|
||||
# Lambda grid
|
||||
lamgrid <- c(-Inf, 2^(-15:25))
|
||||
|
||||
# Gamma grid
|
||||
gammagrid <- sort(1 - sqrt(seq(0, 0.99, .05)))
|
||||
|
Before Width: | Height: | Size: 1.6 MiB |
|
Before Width: | Height: | Size: 1.2 MiB |
|
Before Width: | Height: | Size: 692 KiB |
@@ -1,539 +0,0 @@
|
||||
@article{aastveit2014nowcasting,
|
||||
title = {Nowcasting GDP in real time: A density combination approach},
|
||||
author = {Aastveit, Knut Are and Gerdrup, Karsten R and Jore, Anne Sofie and Thorsrud, Leif Anders},
|
||||
journal = {Journal of Business \& Economic Statistics},
|
||||
volume = {32},
|
||||
number = {1},
|
||||
pages = {48--68},
|
||||
year = {2014},
|
||||
publisher = {Taylor \& Francis}
|
||||
}
|
||||
@incollection{aastveit2019evolution,
|
||||
title = {The Evolution of Forecast Density Combinations in Economics},
|
||||
author = {Aastveit, Knut Are and Mitchell, James and Ravazzolo, Francesco and van Dijk, Herman K},
|
||||
booktitle = {Oxford Research Encyclopedia of Economics and Finance},
|
||||
year = {2019}
|
||||
}
|
||||
@article{atiya2020does,
|
||||
title = {Why does forecast combination work so well?},
|
||||
author = {Atiya, Amir F},
|
||||
journal = {International Journal of Forecasting},
|
||||
volume = {36},
|
||||
number = {1},
|
||||
pages = {197--200},
|
||||
year = {2020},
|
||||
publisher = {Elsevier}
|
||||
}
|
||||
@article{atsalakis2016using,
|
||||
title = {Using computational intelligence to forecast carbon prices},
|
||||
author = {Atsalakis, George S},
|
||||
journal = {Applied Soft Computing},
|
||||
volume = {43},
|
||||
pages = {107--116},
|
||||
year = {2016},
|
||||
publisher = {Elsevier}
|
||||
}
|
||||
@article{bai2020does,
|
||||
title = {Does crude oil futures price really help to predict spot oil price? New evidence from density forecasting},
|
||||
author = {Bai, Lan and Li, Xiafei and Wei, Yu and Wei, Guiwu},
|
||||
journal = {International Journal of Finance \& Economics},
|
||||
year = {2020},
|
||||
publisher = {Wiley Online Library}
|
||||
}
|
||||
@article{benz2009modeling,
|
||||
title = {Modeling the price dynamics of CO2 emission allowances},
|
||||
author = {Benz, Eva and Tr{\"u}ck, Stefan},
|
||||
journal = {Energy Economics},
|
||||
volume = {31},
|
||||
number = {1},
|
||||
pages = {4--15},
|
||||
year = {2009},
|
||||
publisher = {Elsevier}
|
||||
}
|
||||
@article{biau2011sequential,
|
||||
title = {Sequential quantile prediction of time series},
|
||||
author = {Biau, G{\'e}rard and Patra, Beno{\^\i}t},
|
||||
journal = {IEEE Transactions on Information Theory},
|
||||
volume = {57},
|
||||
number = {3},
|
||||
pages = {1664--1674},
|
||||
year = {2011},
|
||||
publisher = {IEEE}
|
||||
}
|
||||
@inproceedings{bousquet2001tracking,
|
||||
title = {Tracking a small set of experts by mixing past posteriors},
|
||||
author = {Bousquet, Olivier and Warmuth, Manfred K},
|
||||
booktitle = {International Conference on Computational Learning Theory},
|
||||
pages = {31--47},
|
||||
year = {2001},
|
||||
organization = {Springer}
|
||||
}
|
||||
@article{bregere2020online,
|
||||
title = {Online hierarchical forecasting for power consumption data},
|
||||
author = {Br{\'e}g{\`e}re, Margaux and Huard, Malo},
|
||||
journal = {arXiv preprint arXiv:2003.00585},
|
||||
year = {2020}
|
||||
}
|
||||
@article{busetti2017quantile,
|
||||
title = {Quantile aggregation of density forecasts},
|
||||
author = {Busetti, Fabio},
|
||||
journal = {Oxford Bulletin of Economics and Statistics},
|
||||
volume = {79},
|
||||
number = {4},
|
||||
pages = {495--512},
|
||||
year = {2017},
|
||||
publisher = {Wiley Online Library}
|
||||
}
|
||||
@book{cesa2006prediction,
|
||||
title = {Prediction, learning, and games},
|
||||
author = {Cesa-Bianchi, Nicolo and Lugosi, G{\'a}bor},
|
||||
year = {2006},
|
||||
publisher = {Cambridge university press}
|
||||
}
|
||||
@article{cesa2012mirror,
|
||||
title = {Mirror descent meets fixed share (and feels no regret)},
|
||||
author = {Cesa-Bianchi, Nicolo and Gaillard, Pierre and Lugosi, G{\'a}bor and Stoltz, Gilles},
|
||||
journal = {Advances in Neural Information Processing Systems},
|
||||
volume = {25},
|
||||
pages = {980--988},
|
||||
year = {2012}
|
||||
}
|
||||
@article{cheng2015forecasting,
|
||||
title = {Forecasting with factor-augmented regression: A frequentist model averaging approach},
|
||||
author = {Cheng, Xu and Hansen, Bruce E},
|
||||
journal = {Journal of Econometrics},
|
||||
volume = {186},
|
||||
number = {2},
|
||||
pages = {280--293},
|
||||
year = {2015},
|
||||
publisher = {Elsevier}
|
||||
}
|
||||
@article{chernozhukov2010quantile,
|
||||
title = {Quantile and probability curves without crossing},
|
||||
author = {Chernozhukov, Victor and Fern{\'a}ndez-Val, Iv{\'a}n and Galichon, Alfred},
|
||||
journal = {Econometrica},
|
||||
volume = {78},
|
||||
number = {3},
|
||||
pages = {1093--1125},
|
||||
year = {2010},
|
||||
publisher = {Wiley Online Library}
|
||||
}
|
||||
@article{devaine2013forecasting,
|
||||
title = {Forecasting electricity consumption by aggregating specialized experts},
|
||||
author = {Devaine, Marie and Gaillard, Pierre and Goude, Yannig and Stoltz, Gilles},
|
||||
journal = {Machine Learning},
|
||||
volume = {90},
|
||||
number = {2},
|
||||
pages = {231--260},
|
||||
year = {2013},
|
||||
publisher = {Springer}
|
||||
}
|
||||
@article{dutta2018modeling,
|
||||
title = {Modeling and forecasting the volatility of carbon emission market: The role of outliers, time-varying jumps and oil price risk},
|
||||
author = {Dutta, Anupam},
|
||||
journal = {Journal of Cleaner Production},
|
||||
volume = {172},
|
||||
pages = {2773--2781},
|
||||
year = {2018},
|
||||
publisher = {Elsevier}
|
||||
}
|
||||
@article{eddelbuettel2014rcpparmadillo,
|
||||
title = {RcppArmadillo: Accelerating R with high-performance C++ linear algebra},
|
||||
author = {Eddelbuettel, Dirk and Sanderson, Conrad},
|
||||
journal = {Computational Statistics \& Data Analysis},
|
||||
volume = {71},
|
||||
pages = {1054--1063},
|
||||
year = {2014},
|
||||
publisher = {Elsevier}
|
||||
}
|
||||
@article{fragoso2018bayesian,
|
||||
title = {Bayesian model averaging: A systematic review and conceptual classification},
|
||||
author = {Fragoso, Tiago M and Bertoli, Wesley and Louzada, Francisco},
|
||||
journal = {International Statistical Review},
|
||||
volume = {86},
|
||||
number = {1},
|
||||
pages = {1--28},
|
||||
year = {2018},
|
||||
publisher = {Wiley Online Library}
|
||||
}
|
||||
@inproceedings{gaillard2014second,
|
||||
title = {A second-order bound with excess losses},
|
||||
author = {Gaillard, Pierre and Stoltz, Gilles and Van Erven, Tim},
|
||||
booktitle = {Conference on Learning Theory},
|
||||
pages = {176--196},
|
||||
year = {2014},
|
||||
organization = {PMLR}
|
||||
}
|
||||
@incollection{gaillard2015forecasting,
|
||||
title = {Forecasting electricity consumption by aggregating experts; how to design a good set of experts},
|
||||
author = {Gaillard, Pierre and Goude, Yannig},
|
||||
booktitle = {Modeling and stochastic learning for forecasting in high dimensions},
|
||||
pages = {95--115},
|
||||
year = {2015},
|
||||
publisher = {Springer}
|
||||
}
|
||||
@inproceedings{gaillard2018efficient,
|
||||
title = {Efficient online algorithms for fast-rate regret bounds under sparsity},
|
||||
author = {Gaillard, Pierre and Wintenberger, Olivier},
|
||||
booktitle = {Advances in Neural Information Processing Systems},
|
||||
pages = {7026--7036},
|
||||
year = {2018}
|
||||
}
|
||||
@article{garcia2020short,
|
||||
title = {Short-term European Union Allowance price forecasting with artificial neural networks},
|
||||
author = {Garc{\'\i}a, Agust{\'\i}n and Jaramillo-Mor{\'a}n, Miguel A},
|
||||
journal = {Entrepreneurship and Sustainability Issues},
|
||||
volume = {8},
|
||||
number = {1},
|
||||
pages = {261},
|
||||
year = {2020}
|
||||
}
|
||||
@article{gneiting2007strictly,
|
||||
title = {Strictly proper scoring rules, prediction, and estimation},
|
||||
author = {Gneiting, Tilmann and Raftery, Adrian E},
|
||||
journal = {Journal of the American statistical Association},
|
||||
volume = {102},
|
||||
number = {477},
|
||||
pages = {359--378},
|
||||
year = {2007},
|
||||
publisher = {Taylor \& Francis}
|
||||
}
|
||||
@article{gneiting2011comparing,
|
||||
title = {Comparing density forecasts using threshold-and quantile-weighted scoring rules},
|
||||
author = {Gneiting, Tilmann and Ranjan, Roopesh},
|
||||
journal = {Journal of Business \& Economic Statistics},
|
||||
volume = {29},
|
||||
number = {3},
|
||||
pages = {411--422},
|
||||
year = {2011},
|
||||
publisher = {Taylor \& Francis}
|
||||
}
|
||||
@article{gneiting2011making,
|
||||
title = {Making and evaluating point forecasts},
|
||||
author = {Gneiting, Tilmann},
|
||||
journal = {Journal of the American Statistical Association},
|
||||
volume = {106},
|
||||
number = {494},
|
||||
pages = {746--762},
|
||||
year = {2011},
|
||||
publisher = {Taylor \& Francis}
|
||||
}
|
||||
@article{gneiting2011quantiles,
|
||||
title = {Quantiles as optimal point forecasts},
|
||||
author = {Gneiting, Tilmann},
|
||||
journal = {International Journal of forecasting},
|
||||
volume = {27},
|
||||
number = {2},
|
||||
pages = {197--207},
|
||||
year = {2011},
|
||||
publisher = {Elsevier}
|
||||
}
|
||||
@article{hansen2008least,
|
||||
title = {Least-squares forecast averaging},
|
||||
author = {Hansen, Bruce E},
|
||||
journal = {Journal of Econometrics},
|
||||
volume = {146},
|
||||
number = {2},
|
||||
pages = {342--350},
|
||||
year = {2008},
|
||||
publisher = {Elsevier}
|
||||
}
|
||||
@article{hao2020modelling,
|
||||
title = {Modelling of carbon price in two real carbon trading markets},
|
||||
author = {Hao, Yan and Tian, Chengshi and Wu, Chunying},
|
||||
journal = {Journal of Cleaner Production},
|
||||
volume = {244},
|
||||
pages = {118556},
|
||||
year = {2020},
|
||||
publisher = {Elsevier}
|
||||
}
|
||||
@article{he1997quantile,
|
||||
title = {Quantile curves without crossing},
|
||||
author = {He, Xuming},
|
||||
journal = {The American Statistician},
|
||||
volume = {51},
|
||||
number = {2},
|
||||
pages = {186--192},
|
||||
year = {1997},
|
||||
publisher = {Taylor \& Francis}
|
||||
}
|
||||
@article{herbster1998tracking,
|
||||
title = {Tracking the best expert},
|
||||
author = {Herbster, Mark and Warmuth, Manfred K},
|
||||
journal = {Machine learning},
|
||||
volume = {32},
|
||||
number = {2},
|
||||
pages = {151--178},
|
||||
year = {1998},
|
||||
publisher = {Springer}
|
||||
}
|
||||
@article{hsiao2014there,
|
||||
title = {Is there an optimal forecast combination?},
|
||||
author = {Hsiao, Cheng and Wan, Shui Ki},
|
||||
journal = {Journal of Econometrics},
|
||||
volume = {178},
|
||||
pages = {294--309},
|
||||
year = {2014},
|
||||
publisher = {Elsevier}
|
||||
}
|
||||
@book{hyndman2018forecasting,
|
||||
title = {Forecasting: principles and practice},
|
||||
author = {Hyndman, Rob J and Athanasopoulos, George},
|
||||
year = {2018},
|
||||
publisher = {OTexts}
|
||||
}
|
||||
@article{jore2010combining,
|
||||
title = {Combining forecast densities from VARs with uncertain instabilities},
|
||||
author = {Jore, Anne Sofie and Mitchell, James and Vahey, Shaun P},
|
||||
journal = {Journal of Applied Econometrics},
|
||||
volume = {25},
|
||||
number = {4},
|
||||
pages = {621--634},
|
||||
year = {2010},
|
||||
publisher = {Wiley Online Library}
|
||||
}
|
||||
@inproceedings{kakade2008generalization,
|
||||
title = {On the Generalization Ability of Online Strongly Convex Programming Algorithms.},
|
||||
author = {Kakade, Sham M and Tewari, Ambuj},
|
||||
booktitle = {NIPS},
|
||||
pages = {801--808},
|
||||
year = {2008}
|
||||
}
|
||||
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|
||||
title = {Generalised density forecast combinations},
|
||||
author = {Kapetanios, G and Mitchell, James and Price, Simon and Fawcett, Nicholas},
|
||||
journal = {Journal of Econometrics},
|
||||
volume = {188},
|
||||
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|
||||
pages = {150--165},
|
||||
year = {2015},
|
||||
publisher = {Elsevier}
|
||||
}
|
||||
@inproceedings{koolen2015second,
|
||||
title = {Second-order quantile methods for experts and combinatorial games},
|
||||
author = {Koolen, Wouter M and Van Erven, Tim},
|
||||
booktitle = {Conference on Learning Theory},
|
||||
pages = {1155--1175},
|
||||
year = {2015}
|
||||
}
|
||||
@article{koop2013forecasting,
|
||||
title = {Forecasting the European carbon market},
|
||||
author = {Koop, Gary and Tole, Lise},
|
||||
journal = {Journal of the Royal Statistical Society: Series A (Statistics in Society)},
|
||||
volume = {176},
|
||||
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|
||||
pages = {723--741},
|
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year = {2013},
|
||||
publisher = {Wiley Online Library}
|
||||
}
|
||||
@article{korotin2019integral,
|
||||
title = {Integral Mixabilty: a Tool for Efficient Online Aggregation of Functional and Probabilistic Forecasts},
|
||||
author = {Korotin, Alexander and V'yugin, Vladimir and Burnaev, Evgeny},
|
||||
journal = {arXiv preprint arXiv:1912.07048},
|
||||
year = {2019}
|
||||
}
|
||||
@inproceedings{korotin2020mixing,
|
||||
title = {Mixing past predictions},
|
||||
author = {Korotin, Alexander and V’yugin, Vladimir and Burnaev, Evgeny},
|
||||
booktitle = {Conformal and Probabilistic Prediction and Applications},
|
||||
pages = {171--188},
|
||||
year = {2020},
|
||||
organization = {PMLR}
|
||||
}
|
||||
@article{lichtendahl2013better,
|
||||
title = {Is it better to average probabilities or quantiles?},
|
||||
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|
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|
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|
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|
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|
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|
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|
||||
}
|
||||
@article{lin2018multi,
|
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title = {A multi-model combination approach for probabilistic wind power forecasting},
|
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author = {Lin, You and Yang, Ming and Wan, Can and Wang, Jianhui and Song, Yonghua},
|
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}
|
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|
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}
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|
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title = {Jackknife model averaging for quantile regressions},
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author = {Lu, Xun and Su, Liangjun},
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year = {2015},
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publisher = {Elsevier}
|
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}
|
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|
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title = {PCA Forecast Averaging—Predicting Day-Ahead and Intraday Electricity Prices},
|
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author = {Maciejowska, Katarzyna and Uniejewski, Bartosz and Serafin, Tomasz},
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publisher = {Multidisciplinary Digital Publishing Institute}
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}
|
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|
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title = {Lipschitz adaptivity with multiple learning rates in online learning},
|
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author = {Mhammedi, Zakaria and Koolen, Wouter M and Van Erven, Tim},
|
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journal = {arXiv preprint arXiv:1902.10797},
|
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year = {2019}
|
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}
|
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@article{nowotarski2018recent,
|
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title = {Recent advances in electricity price forecasting: A review of probabilistic forecasting},
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author = {Nowotarski, Jakub and Weron, Rafa{\l}},
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year = {2018},
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publisher = {Elsevier}
|
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}
|
||||
@article{opschoor2017combining,
|
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title = {Combining density forecasts using focused scoring rules},
|
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author = {Opschoor, Anne and Van Dijk, Dick and van der Wel, Michel},
|
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journal = {Journal of Applied Econometrics},
|
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|
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}
|
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title = {Forecasting: theory and practice},
|
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author = {Petropoulos, Fotios and Apiletti, Daniele and Assimakopoulos, Vassilios and Babai, Mohamed Zied and Barrow, Devon K and Bergmeir, Christoph and Bessa, Ricardo J and Boylan, John E and Browell, Jethro and Carnevale, Claudio and others},
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journal = {arXiv preprint arXiv:2012.03854},
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year = {2020}
|
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}
|
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|
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title = {Using Bayesian model averaging to calibrate forecast ensembles},
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author = {Raftery, Adrian E and Gneiting, Tilmann and Balabdaoui, Fadoua and Polakowski, Michael},
|
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journal = {Monthly weather review},
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pages = {1155--1174},
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year = {2005}
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}
|
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title = {Modeling and forecasting the volatility of carbon dioxide emission allowance prices: A review and comparison of modern volatility models},
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author = {Segnon, Mawuli and Lux, Thomas and Gupta, Rangan},
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volume = {69},
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year = {2017},
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publisher = {Elsevier}
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}
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@article{thorey2017online,
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title = {Online learning with the Continuous Ranked Probability Score for ensemble forecasting},
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author = {Thorey, Jean and Mallet, Vivien and Baudin, Paul},
|
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journal = {Quarterly Journal of the Royal Meteorological Society},
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volume = {143},
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pages = {521--529},
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year = {2017},
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publisher = {Wiley Online Library}
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}
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title = {Ensemble forecast of photovoltaic power with online CRPS learning},
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author = {Thorey, Jean and Chaussin, Christophe and Mallet, Vivien},
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journal = {International Journal of Forecasting},
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volume = {34},
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year = {2018},
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publisher = {Elsevier}
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}
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title = {Markowitz meets Talmud: A combination of sophisticated and naive diversification strategies},
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author = {Tu, Jun and Zhou, Guofu},
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}
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title = {Online Aggregation of Probabilistic Forecasts Based on the Continuous Ranked Probability Score},
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}
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volume = {171},
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year = {2018},
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publisher = {Elsevier}
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}
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}
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publisher = {SIAM}
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}
|
||||
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|
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author = {Wang, Yuedong},
|
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year = {2011},
|
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publisher = {CRC Press}
|
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}
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journal = {arXiv preprint arXiv:1910.12209},
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year = {2019}
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}
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pages = {119--141},
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year = {2017},
|
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publisher = {Springer}
|
||||
}
|
||||
@article{zamo2020sequential,
|
||||
title = {Sequential Aggregation of Probabilistic Forecasts--Applicaton to Wind Speed Ensemble Forecasts},
|
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author = {Zamo, Micha{\"e}l and Bel, Liliane and Mestre, Olivier},
|
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journal = {arXiv preprint arXiv:2005.03540},
|
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year = {2020}
|
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}
|
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@article{zhang2020load,
|
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title = {Load probability density forecasting by transforming and combining quantile forecasts},
|
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author = {Zhang, Shu and Wang, Yi and Zhang, Yutian and Wang, Dan and Zhang, Ning},
|
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journal = {Applied Energy},
|
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volume = {277},
|
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pages = {115600},
|
||||
year = {2020},
|
||||
publisher = {Elsevier}
|
||||
}
|
||||
@@ -1,261 +0,0 @@
|
||||
/*-- scss:defaults --*/
|
||||
|
||||
// Custom colours and variables
|
||||
|
||||
$jet: #131516;
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||||
$accent: #107895;
|
||||
$accent2: #9a2515;
|
||||
// $accent2: #e64173;
|
||||
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|
||||
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|
||||
Note: This theme uses the Roboto font family, which it imports from Google
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||||
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|
||||
you can use a local installation of Roboto, this is generally not
|
||||
recommended since the weighting will likely be wrong (probably too
|
||||
light). OTOH, importing from Google Fonts can cause some issues in
|
||||
certain secure environments due the external CDN (see:
|
||||
https://github.com/grantmcdermott/quarto-revealjs-clean/issues/7). If
|
||||
that's the case for you, simply comment out the `@import url(...)` line
|
||||
below and it will default for the default Sans Serif font on your system
|
||||
(e.g., Helvetica on a Mac). Circling back to the earlier point about
|
||||
preserving consistent font weights, you may also wish to remove "Roboto"
|
||||
from the choice set if the family is installed locally.
|
||||
*/
|
||||
@import url(https://fonts.googleapis.com/css?family=Roboto:200,200i,300,300i,350,350i,400,400i);
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||||
$font-family-sans-serif: "Roboto", sans-serif !default;
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||||
$presentation-heading-font: "Roboto", sans-serif !default;
|
||||
|
||||
$presentation-heading-color: $jet !default;
|
||||
$presentation-heading-font-weight: lighter;
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||||
//$presentation-heading-line-height: 2;
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||||
//$presentation-block-margin: 28px;
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||||
$presentation-font-size-root: 32px;
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||||
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// colors
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//$body-bg: #f0f1eb !default;
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$body-color: $jet !default;
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||||
$link-color: $accent !default;
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||||
$selection-bg: #26351c !default;
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||||
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||||
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||||
/*-- scss:rules --*/
|
||||
|
||||
.reveal a {
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||||
line-height: 1.5em;
|
||||
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||||
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.reveal p {
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||||
// font-weight: 300;
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||||
font-weight: lighter;
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||||
margin-top: 1.25em;
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||||
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||||
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||||
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||||
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|
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text-align: left;
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||||
color: $body-color;
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||||
font-size: 1.4em;
|
||||
// font-weight: 350;
|
||||
font-weight: lighter;
|
||||
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|
||||
|
||||
.subtitle {
|
||||
color: $accent;
|
||||
font-style: italic;
|
||||
margin-top: 0em;
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||||
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|
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|
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// font-size: 80%;
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// color: #7F7F7F;
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.author,
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|
||||
color: $body-color;
|
||||
}
|
||||
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.quarto-title-authors {
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display: flex;
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||||
justify-content: left;
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.quarto-title-author {
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||||
padding-left: 0em;
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||||
padding-right: 0em;
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width: 100%;
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.reveal h2 {
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font-weight: lighter;
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font-size: 1.4em;
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}
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.reveal h3 {
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color: $accent;
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font-style: italic;
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font-weight: lighter;
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font-size: 0.95em;
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// font-weight: 350;
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font-weight: normal;
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margin-top: 1.25em;
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// alerts etc.
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.alert {
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font-weight: lighter;
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padding-left: 16px;
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li::marker {
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color: mix($accent, white, 70%);
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}
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||||
list-style: none;
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li:before {
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content: $right-arrow;
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color: mix($accent, white, 60%);
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width: 1em;
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margin-left: -1em;
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margin-right: 0.5em;
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font-weight: lighter;
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padding-left: 16px;
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li::marker {
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color: $accent;
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top: 6px;
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display: flex;
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justify-content: flex-end;
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align-items: flex-start;
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pointer-events: none;
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.reveal .slide-menu-button > * {
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pointer-events: auto;
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// Same for chalkboard buttons (with an offset)
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.reveal .slide-chalkboard-buttons {
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position: fixed;
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top: 12px;
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right: 24px;
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display: flex;
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justify-content: flex-end;
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align-items: flex-start;
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pointer-events: none;
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.reveal .slide-chalkboard-buttons > * {
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pointer-events: auto;
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// Beamer-style button link environment
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.button {
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display: inline-block;
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padding: 6px 12px;
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font-size: 14px;
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line-height: 1.42857143;
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text-align: center;
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white-space: nowrap;
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background-color: $accent;
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color: #fff !important;
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||||
|
||||
.button::before {
|
||||
content: "▶";
|
||||
margin-right: 5px;
|
||||
}
|
||||
|
||||
// Special catch for etable environment to ensure these table images
|
||||
// don't overflow the slide.
|
||||
// See: https://lrberge.github.io/fixest/articles/etable_new_features.html
|
||||
|
||||
.etable {
|
||||
width: 100%;
|
||||
height: calc(100% - 3em); /* Adjust 3em based on the height of your header, if necessary */
|
||||
display: flex;
|
||||
align-items: center;
|
||||
justify-content: center;
|
||||
}
|
||||
|
||||
.etable img {
|
||||
max-width: 100%;
|
||||
max-height: 100%;
|
||||
width: auto;
|
||||
height: auto;
|
||||
object-fit: contain;
|
||||
}
|
||||
@@ -1,11 +0,0 @@
|
||||
/*-- scss:defaults --*/
|
||||
|
||||
$body-bg: #ffffff;
|
||||
$body-color: #7a6f69;
|
||||
$link-color: #005088;
|
||||
$selection-color: #00b0dc;
|
||||
|
||||
$presentation-heading-color: $selection-color;
|
||||
$tabset-border-color: #bbb3b0;
|
||||
|
||||
/*-- scss:rules --*/
|
||||
17
_extensions/quarto-ext/pointer/_extension.yml
Normal file
@@ -0,0 +1,17 @@
|
||||
title: Pointer
|
||||
author: Posit Software, PBC
|
||||
version: 0.1.0
|
||||
quarto-required: ">=1.2.198"
|
||||
contributes:
|
||||
revealjs-plugins:
|
||||
- name: RevealPointer
|
||||
script: pointer.js
|
||||
stylesheet: pointer.css
|
||||
config:
|
||||
pointer:
|
||||
key: "q"
|
||||
alwaysVisible: false
|
||||
hideDelay: 3000
|
||||
color: "#202020FF"
|
||||
scaleFactor: 0.03 # 3% of viewport height
|
||||
icon: "fa fa-hand-point-up"
|
||||
41
_extensions/quarto-ext/pointer/pointer.css
Normal file
@@ -0,0 +1,41 @@
|
||||
:root {
|
||||
--pointer-scale-factor: 0.025;
|
||||
/* 2.5% of viewport height */
|
||||
}
|
||||
|
||||
.cursor-dot,
|
||||
.cursor-dot-outline {
|
||||
pointer-events: none;
|
||||
position: absolute;
|
||||
top: 0;
|
||||
left: 0;
|
||||
opacity: 0;
|
||||
transform: translate(-30%, 0%);
|
||||
transition: opacity 0.4s ease-in-out;
|
||||
z-index: 99;
|
||||
}
|
||||
|
||||
.cursor-dot {
|
||||
font-family: "Font Awesome 6 Free", "Font Awesome 6 Brands", "Font Awesome 5 Free", "Font Awesome 5 Brands";
|
||||
font-weight: 900;
|
||||
color: red;
|
||||
font-size: calc(var(--pointer-scale-factor) * 100vh);
|
||||
}
|
||||
|
||||
.cursor-dot.visible {
|
||||
opacity: 0.8 !important;
|
||||
}
|
||||
|
||||
.cursor-dot.hidden {
|
||||
opacity: 0 !important;
|
||||
}
|
||||
|
||||
.no-cursor {
|
||||
cursor: none;
|
||||
}
|
||||
|
||||
.no-cursor a,
|
||||
.no-cursor div,
|
||||
.no-cursor span {
|
||||
cursor: none;
|
||||
}
|
||||
1
_extensions/quarto-ext/pointer/pointer.js
Normal file
@@ -0,0 +1 @@
|
||||
var RevealPointer=function(){"use strict";var e={backspace:8,tab:9,enter:13,shift:16,ctrl:17,alt:18,pausebreak:19,capslock:20,esc:27,space:32,pageup:33,pagedown:34,end:35,home:36,leftarrow:37,uparrow:38,rightarrow:39,downarrow:40,insert:45,delete:46,0:48,1:49,2:50,3:51,4:52,5:53,6:54,7:55,8:56,9:57,a:65,b:66,c:67,d:68,e:69,f:70,g:71,h:72,i:73,j:74,k:75,l:76,m:77,n:78,o:79,p:80,q:81,r:82,s:83,t:84,u:85,v:86,w:87,x:88,y:89,z:90,leftwindowkey:91,rightwindowkey:92,selectkey:93,numpad0:96,numpad1:97,numpad2:98,numpad3:99,numpad4:100,numpad5:101,numpad6:102,numpad7:103,numpad8:104,numpad9:105,multiply:106,add:107,subtract:109,decimalpoint:110,divide:111,f1:112,f2:113,f3:114,f4:115,f5:116,f6:117,f7:118,f8:119,f9:120,f10:121,f11:122,f12:123,numlock:144,scrolllock:145,semicolon:186,equalsign:187,comma:188,dash:189,period:190,forwardslash:191,graveaccent:192,openbracket:219,backslash:220,closebracket:221,singlequote:222};return function(){var t={},o=!1,a=null,n={x:0,y:0,isVisible:!1},i={x:0,y:0,scale:1},hideTimer=null;function l(o){var a;null==(t=o.pointer||{}).key?t.key="q":t.key=t.key.toLowerCase(),null!=t.tailLength&&"number"==typeof t.tailLength||(t.tailLength=10),null!=t.color&&"string"==typeof t.color||(t.color="red"),null!=t.alwaysVisible&&"boolean"==typeof t.alwaysVisible||(t.alwaysVisible=!1),null!=t.icon&&"string"==typeof t.icon||(t.icon="fa-solid fa-arrow-pointer"),null!=t.hideDelay&&"number"==typeof t.hideDelay||(t.hideDelay=3e3),null!=t.scaleFactor&&"number"==typeof t.scaleFactor||(t.scaleFactor=0.025),t.keyCode=(a=t.key,e[a])}function updatePointerSize(){document.documentElement.style.setProperty("--pointer-scale-factor",t.scaleFactor)}function showPointer(){if(!n.isVisible){n.isVisible=!0;a.classList.remove("hidden");setTimeout(()=>{a.classList.add("visible")},10);if(hideTimer){clearTimeout(hideTimer);hideTimer=null}if(!t.alwaysVisible){hideTimer=setTimeout(hidePointer,t.hideDelay)}}}function hidePointer(){if(n.isVisible){n.isVisible=!1;a.classList.remove("visible");if(hideTimer){clearTimeout(hideTimer);hideTimer=null}}}function s(){a.style.top="".concat((n.y-i.y)/i.scale,"px"),a.style.left="".concat((n.x-i.x)/i.scale,"px")}function c(e){n.x=e.pageX,n.y=e.pageY;var t=document.body.style.transform;""!==t?(i.x=Number.parseInt(/translate\((.*)px,/gm.exec(t)[1]),i.y=Number.parseInt(/px,\s(.*)px\)/gm.exec(t)[1]),i.scale=Number.parseFloat(/scale\((.)\)/gm.exec(t)[1])):(i.x=0,i.y=0,i.scale=1),requestAnimationFrame(s);if(o&&!t.alwaysVisible){showPointer()}}function r(){(o=!o)?(document.addEventListener("mousemove",c),document.body.classList.add("no-cursor"),showPointer()):(document.removeEventListener("mousemove",c),document.body.classList.remove("no-cursor"),hidePointer())}return{id:"pointer",init:function(e){var o;l(e.getConfig()),updatePointerSize(),t.alwaysVisible?r():e.addKeyBinding({keyCode:t.keyCode,key:t.key},(function(){r()})),(o=document.createElement("i")).className="cursor-dot "+t.icon,o.style.color=t.color,t.alwaysVisible&&o.classList.add("visible"),document.body.appendChild(o),a=o,window.addEventListener("resize",updatePointerSize)}}}}();
|
||||
90
assets/01_common.R
Normal file
@@ -0,0 +1,90 @@
|
||||
text_size <- 16
|
||||
linesize <- 1
|
||||
width <- 12
|
||||
height <- 6
|
||||
|
||||
# col_lightgray <- "#e7e7e7"
|
||||
# col_blue <- "#F24159"
|
||||
# col_b_smooth <- "#F7CE14"
|
||||
# col_p_smooth <- "#58A64A"
|
||||
# col_pointwise <- "#772395"
|
||||
# col_b_constant <- "#BF236D"
|
||||
# col_p_constant <- "#F6912E"
|
||||
# col_optimum <- "#666666"
|
||||
|
||||
# https://www.schemecolor.com/retro-rainbow-pastels.php
|
||||
col_lightgray <- "#e7e7e7"
|
||||
col_blue <- "#F24159"
|
||||
col_b_smooth <- "#5391AE"
|
||||
col_p_smooth <- "#85B464"
|
||||
col_pointwise <- "#E2D269"
|
||||
col_b_constant <- "#7A4E8A"
|
||||
col_p_constant <- "#BC677B"
|
||||
col_optimum <- "#666666"
|
||||
col_auto <- "#EA915E"
|
||||
|
||||
T_selection <- c(32, 128, 512)
|
||||
|
||||
# Lambda grid
|
||||
lamgrid <- c(-Inf, 2^(-15:25))
|
||||
|
||||
# Gamma grid
|
||||
gammagrid <- sort(1 - sqrt(seq(0, 0.99, .05)))
|
||||
|
||||
material_pals <- c(
|
||||
"red", "pink", "purple", "deep-purple", "indigo",
|
||||
"blue", "light-blue", "cyan", "teal", "green", "light-green", "lime",
|
||||
"yellow", "amber", "orange", "deep-orange", "brown", "grey", "blue-grey"
|
||||
)
|
||||
cols <- purrr::map(material_pals, ~ ggsci::pal_material(.x)(10)) %>%
|
||||
purrr::reduce(cbind)
|
||||
colnames(cols) <- material_pals
|
||||
|
||||
cols %>%
|
||||
as_tibble() %>%
|
||||
mutate(idx = as.factor(1:10)) %>%
|
||||
pivot_longer(-idx, names_to = "var", values_to = "val") %>%
|
||||
mutate(var = factor(var, levels = material_pals[19:1])) %>%
|
||||
ggplot() +
|
||||
xlab(NULL) +
|
||||
ylab(NULL) +
|
||||
geom_tile(aes(x = idx, y = var, fill = val)) +
|
||||
scale_fill_identity() +
|
||||
scale_x_discrete(expand = c(0, 0)) +
|
||||
scale_y_discrete(expand = c(0, 0)) +
|
||||
theme_minimal() -> plot_cols
|
||||
|
||||
col_gas <- "blue"
|
||||
col_eua <- "green"
|
||||
col_oil <- "amber"
|
||||
col_coal <- "brown"
|
||||
|
||||
col_scale2 <- function(x, rng_t) {
|
||||
ret <- x
|
||||
for (i in seq_along(x)) {
|
||||
if (x[i] < rng_t[1]) {
|
||||
ret[i] <- col_scale(rng_t[1])
|
||||
} else if (x[i] > rng_t[2]) {
|
||||
ret[i] <- col_scale(rng_t[2])
|
||||
} else {
|
||||
ret[i] <- col_scale(x[i])
|
||||
}
|
||||
}
|
||||
return(ret)
|
||||
}
|
||||
|
||||
rng_t <- c(-5, 5)
|
||||
h_sub <- c(1, 5, 30)
|
||||
|
||||
col_scale <- scales::gradient_n_pal(
|
||||
c(
|
||||
cols[5, "green"],
|
||||
cols[5, "light-green"],
|
||||
cols[5, "yellow"],
|
||||
# cols[5, "amber"],
|
||||
cols[5, "orange"],
|
||||
# cols[5, "deep-orange"],
|
||||
cols[5, "red"]
|
||||
),
|
||||
values = seq(rng_t[1], rng_t[2], length.out = 5)
|
||||
)
|
||||
BIN
assets/Renewable_Energy_Forecasting.png
Normal file
|
After Width: | Height: | Size: 1.6 MiB |
BIN
assets/allisonhorst/hiding.png
Normal file
|
After Width: | Height: | Size: 1.9 MiB |
BIN
assets/allisonhorst/not_normal.png
Normal file
|
After Width: | Height: | Size: 250 KiB |
BIN
assets/allisonhorst/the_beginning.png
Normal file
|
After Width: | Height: | Size: 923 KiB |
BIN
assets/allisonhorst/the_beginning_cropped.png
Normal file
|
After Width: | Height: | Size: 926 KiB |
|
Before Width: | Height: | Size: 2.3 MiB After Width: | Height: | Size: 2.3 MiB |
|
Before Width: | Height: | Size: 3.1 MiB After Width: | Height: | Size: 3.1 MiB |
BIN
assets/crps_learning/forget.png
Normal file
|
After Width: | Height: | Size: 58 KiB |
BIN
assets/crps_learning/pre_vs_post.gif
Normal file
|
After Width: | Height: | Size: 1.7 MiB |
BIN
assets/crps_learning/pre_vs_post_kstep.gif
Normal file
|
After Width: | Height: | Size: 891 KiB |
BIN
assets/crps_learning/pre_vs_post_lambda.gif
Normal file
|
After Width: | Height: | Size: 934 KiB |
|
Before Width: | Height: | Size: 4.2 MiB After Width: | Height: | Size: 4.2 MiB |
BIN
assets/crps_learning/weights_kstep.gif
Normal file
|
After Width: | Height: | Size: 862 KiB |
BIN
assets/crps_learning/weights_lambda.gif
Normal file
|
After Width: | Height: | Size: 636 KiB |
33034
assets/crps_learning/weights_plot/cdf_data.csv
Normal file
206
assets/crps_learning/weights_plot/index.qmd
Normal file
@@ -0,0 +1,206 @@
|
||||
---
|
||||
title: "CDF Weights"
|
||||
date: 2025-07-10
|
||||
format:
|
||||
revealjs:
|
||||
embed-resources: true
|
||||
execute:
|
||||
daemon: false
|
||||
highlight-style: github
|
||||
---
|
||||
|
||||
|
||||
```{ojs}
|
||||
d3 = require("d3@7")
|
||||
```
|
||||
|
||||
```{ojs}
|
||||
cdf_data = FileAttachment("cdf_data.csv").csv({ typed: true })
|
||||
```
|
||||
|
||||
```{ojs}
|
||||
function updateChartInner(g, x, y, linesGroup, color, line, data) {
|
||||
// Update axes with transitions
|
||||
x.domain(d3.extent(data, d => d.x));
|
||||
g.select(".x-axis").transition().duration(1500).call(d3.axisBottom(x).ticks(10));
|
||||
y.domain([0, d3.max(data, d => d.y)]);
|
||||
g.select(".y-axis").transition().duration(1500).call(d3.axisLeft(y).ticks(5));
|
||||
|
||||
// Group data by basis function
|
||||
const dataByFunction = Array.from(d3.group(data, d => d.b));
|
||||
const keyFn = d => d[0];
|
||||
|
||||
// Update basis function lines
|
||||
const u = linesGroup.selectAll("path").data(dataByFunction, keyFn);
|
||||
u.join(
|
||||
enter => enter.append("path").attr("fill","none").attr("stroke-width",3)
|
||||
.attr("stroke", (_, i) => color(i)).attr("d", d => line(d[1].map(pt => ({x: pt.x, y: 0}))))
|
||||
.style("opacity",0),
|
||||
update => update,
|
||||
exit => exit.transition().duration(1000).style("opacity",0).remove()
|
||||
)
|
||||
.transition().duration(1000)
|
||||
.attr("d", d => line(d[1]))
|
||||
.attr("stroke", (_, i) => color(i))
|
||||
.style("opacity",1);
|
||||
}
|
||||
|
||||
chart = {
|
||||
// State variable for selected mu parameter
|
||||
let selectedMu = 1;
|
||||
|
||||
const filteredData = () => cdf_data.filter(d =>
|
||||
Math.abs(selectedMu - d.mu) < 0.001
|
||||
);
|
||||
|
||||
const container = d3.create("div")
|
||||
.style("max-width", "none")
|
||||
.style("width", "100%");
|
||||
|
||||
const controlsContainer = container.append("div")
|
||||
.style("display", "flex")
|
||||
.style("gap", "20px")
|
||||
.style("align-items", "center");
|
||||
|
||||
// Single slider control for mu
|
||||
const sliderContainer = controlsContainer.append('div')
|
||||
.style('display','flex')
|
||||
.style('align-items','center')
|
||||
.style('gap','10px')
|
||||
.style('flex','1');
|
||||
|
||||
sliderContainer.append('label')
|
||||
.text('Naive:')
|
||||
.style('font-size','20px');
|
||||
|
||||
const muSlider = sliderContainer.append('input')
|
||||
.attr('type','range')
|
||||
.attr('min', 0)
|
||||
.attr('max', 1)
|
||||
.attr('step', 0.1)
|
||||
.property('value', selectedMu)
|
||||
.on('input', function(event) {
|
||||
selectedMu = +this.value;
|
||||
muDisplay.text(selectedMu.toFixed(1));
|
||||
updateChart(filteredData());
|
||||
})
|
||||
.style('width', '100%')
|
||||
//.style('-webkit-appearance', 'none')
|
||||
.style('appearance', 'none')
|
||||
.style('height', '8px')
|
||||
.style('background', '#BDBDBDFF');
|
||||
|
||||
const muDisplay = sliderContainer.append('span')
|
||||
.text(selectedMu.toFixed(1))
|
||||
.style('font-size','20px');
|
||||
|
||||
// Add Reset button
|
||||
controlsContainer.append('button')
|
||||
.text('Reset')
|
||||
.style('font-size', '20px')
|
||||
.style('align-self', 'center')
|
||||
.style('margin-left', 'auto')
|
||||
.on('click', () => {
|
||||
selectedMu = 0.5;
|
||||
muSlider.property('value', selectedMu);
|
||||
muDisplay.text(selectedMu.toFixed(1));
|
||||
updateChart(filteredData());
|
||||
});
|
||||
|
||||
// Build SVG
|
||||
const width = 800;
|
||||
const height = 450;
|
||||
const margin = {top: 40, right: 20, bottom: 40, left: 40};
|
||||
const innerWidth = width - margin.left - margin.right;
|
||||
const innerHeight = height - margin.top - margin.bottom;
|
||||
|
||||
// Set controls container width to match SVG plot width
|
||||
controlsContainer.style("max-width", "none").style("width", "100%");
|
||||
// Distribute each control evenly and make sliders full-width
|
||||
controlsContainer.selectAll("div").style("flex", "1").style("min-width", "0px");
|
||||
controlsContainer.selectAll("input").style("width", "100%").style("box-sizing", "border-box");
|
||||
|
||||
// Create scales
|
||||
const x = d3.scaleLinear()
|
||||
.range([0, innerWidth]);
|
||||
|
||||
const y = d3.scaleLinear()
|
||||
.range([innerHeight, 0]);
|
||||
|
||||
// Create a color scale for the basis functions
|
||||
const color = d3.scaleOrdinal(["#80C684FF", "#FFD44EFF", "#D81A5FFF"]);
|
||||
|
||||
// Create SVG
|
||||
const svg = d3.create("svg")
|
||||
.attr("width", "100%")
|
||||
.attr("height", "auto")
|
||||
.attr("viewBox", [0, 0, width, height])
|
||||
.attr("preserveAspectRatio", "xMidYMid meet")
|
||||
.attr("style", "max-width: 100%; height: auto;");
|
||||
|
||||
// Create the chart group
|
||||
const g = svg.append("g")
|
||||
.attr("transform", `translate(${margin.left},${margin.top})`);
|
||||
|
||||
// Add axes
|
||||
const xAxis = g.append("g")
|
||||
.attr("transform", `translate(0,${innerHeight})`)
|
||||
.attr("class", "x-axis")
|
||||
.call(d3.axisBottom(x).ticks(10))
|
||||
.style("font-size", "20px");
|
||||
|
||||
const yAxis = g.append("g")
|
||||
.attr("class", "y-axis")
|
||||
.call(d3.axisLeft(y).ticks(5))
|
||||
.style("font-size", "20px");
|
||||
|
||||
// Add a horizontal line at y = 0
|
||||
g.append("line")
|
||||
.attr("x1", 0)
|
||||
.attr("x2", innerWidth)
|
||||
.attr("y1", y(0))
|
||||
.attr("y2", y(0))
|
||||
.attr("stroke", "#000")
|
||||
.attr("stroke-opacity", 0.2);
|
||||
|
||||
// Add gridlines
|
||||
g.append("g")
|
||||
.attr("class", "grid-lines")
|
||||
.selectAll("line")
|
||||
.data(y.ticks(5))
|
||||
.join("line")
|
||||
.attr("x1", 0)
|
||||
.attr("x2", innerWidth)
|
||||
.attr("y1", d => y(d))
|
||||
.attr("y2", d => y(d))
|
||||
.attr("stroke", "#ccc")
|
||||
.attr("stroke-opacity", 0.5);
|
||||
|
||||
// Create a line generator
|
||||
const line = d3.line()
|
||||
.x(d => x(d.x))
|
||||
.y(d => y(d.y))
|
||||
.curve(d3.curveBasis);
|
||||
|
||||
// Group to contain the basis function lines
|
||||
const linesGroup = g.append("g")
|
||||
.attr("class", "basis-functions");
|
||||
|
||||
// Store the current basis functions for transition
|
||||
let currentBasisFunctions = new Map();
|
||||
|
||||
// Function to update the chart with new data
|
||||
function updateChart(data) {
|
||||
updateChartInner(g, x, y, linesGroup, color, line, data);
|
||||
}
|
||||
|
||||
// Store the update function
|
||||
svg.node().update = updateChart;
|
||||
|
||||
// Initial render
|
||||
updateChart(filteredData());
|
||||
|
||||
container.node().appendChild(svg.node());
|
||||
return container.node();
|
||||
}
|
||||
```
|
||||
78
assets/crps_learning/weights_plot/make_cdf_data.R
Normal file
@@ -0,0 +1,78 @@
|
||||
library(tidyverse)
|
||||
|
||||
source("assets/01_common.R")
|
||||
|
||||
set.seed(2002)
|
||||
# Experts
|
||||
N <- 2
|
||||
# Observations
|
||||
T <- 2^5
|
||||
# Size of probability grid
|
||||
P <- 999
|
||||
prob_grid <- 1:P / (P + 1)
|
||||
|
||||
# Realized observations
|
||||
y <- rnorm(T)
|
||||
|
||||
# Deviation of the experts
|
||||
dev <- c(-1, 3)
|
||||
experts_sd <- c(1, sqrt(4))
|
||||
|
||||
# Expert predictions
|
||||
experts <- array(dim = c(P, N))
|
||||
|
||||
seq(-5, 10, length.out = P) -> x_grid
|
||||
|
||||
experts[, 1] <- qnorm(prob_grid, mean = dev[1], sd = experts_sd[1])
|
||||
experts[, 2] <- qnorm(prob_grid, mean = dev[2], sd = experts_sd[2])
|
||||
|
||||
experts <- rbind(c(rep(min(experts), N)), experts)
|
||||
experts <- rbind(experts, c(rep(max(experts), N)))
|
||||
prob_grid <- c(0, prob_grid, 1)
|
||||
|
||||
naive <- 1
|
||||
|
||||
df <- data.frame(
|
||||
x = rep(prob_grid, each = N),
|
||||
y = c(t(experts)),
|
||||
expert = rep(1:N, (P + 2)),
|
||||
naive = rep(naive, (P + 2) * N)
|
||||
)
|
||||
|
||||
naive <- seq(0, 1, length.out = 11)
|
||||
|
||||
dfs <- list()
|
||||
|
||||
df_old <- df
|
||||
|
||||
for (i in seq_along(naive)) {
|
||||
df_old$naive <- naive[i]
|
||||
|
||||
df_new <- data.frame(
|
||||
x = prob_grid,
|
||||
y = (experts[, 1] * (naive[i] * (0.5) + (1 - naive[i]) * (1 - prob_grid)) + (naive[i] * 0.5 + (1 - naive[i]) * (prob_grid)) * experts[, 2]),
|
||||
expert = 3,
|
||||
naive = rep(naive[i], (P + 2))
|
||||
)
|
||||
|
||||
dfs[[i + 1]] <- bind_rows(df_old, df_new)
|
||||
}
|
||||
|
||||
dfs <- reduce(dfs, bind_rows)
|
||||
|
||||
colnames(dfs) <- c("y", "x", "b", "mu")
|
||||
|
||||
dfs %>%
|
||||
ggplot(aes(x = x, y = y, color = factor(b))) +
|
||||
geom_line() +
|
||||
labs(
|
||||
title = "Expert Predictions",
|
||||
x = "Probability Grid",
|
||||
y = "Predicted Value"
|
||||
) +
|
||||
theme_minimal() +
|
||||
scale_color_brewer(palette = "Set1") +
|
||||
theme(legend.position = "top") +
|
||||
facet_wrap(. ~ mu, ncol = 3)
|
||||
|
||||
write_csv(dfs, "assets/crps_learning/weights_plot/cdf_data.csv")
|
||||
BIN
assets/crps_learning/weights_preprocessed.rda
Normal file
1387
assets/hecf_logo.svg
Normal file
|
After Width: | Height: | Size: 84 KiB |
1382
assets/hecf_logo_reduced.svg
Normal file
|
After Width: | Height: | Size: 64 KiB |
1364
assets/hecf_signet.svg
Normal file
|
After Width: | Height: | Size: 42 KiB |
197
assets/library.bib
Normal file
@@ -0,0 +1,197 @@
|
||||
@article{berrisch2023modeling,
|
||||
title = {Modeling volatility and dependence of European carbon and energy prices},
|
||||
author = {Jonathan Berrisch and Sven Pappert and Florian Ziel and Antonia Arsova},
|
||||
year = {2023},
|
||||
month = {3},
|
||||
journal = {Finance Research Letters},
|
||||
publisher = {Elsevier BV},
|
||||
volume = {52},
|
||||
pages = {103503},
|
||||
doi = {10.1016/j.frl.2022.103503},
|
||||
issn = {1544-6123},
|
||||
url = {https://arxiv.org/pdf/2208.14311},
|
||||
abstract = {We study the prices of European Emission Allowances (EUA), whereby we analyze their uncertainty and dependencies on related energy prices (natural gas, coal, and oil). We propose a probabilistic multivariate conditional time series model with a VECM-Copula-GARCH structure which exploits key characteristics of the data. Data are normalized with respect to inflation and carbon emissions to allow for proper cross-series evaluation. The forecasting performance is evaluated in an extensive rolling-window forecasting study, covering eight years out-of-sample. We discuss our findings for both levels- and log-transformed data, focusing on time-varying correlations, and in view of the Russian invasion of Ukraine.},
|
||||
keywords = {Carbon prices, Conditional volatility, Copula, Emission allowances, Energy markets, Forecasting, Multivariate modeling, Time series}
|
||||
}
|
||||
@article{marcjasz2022distributional,
|
||||
title = {Distributional neural networks for electricity price forecasting},
|
||||
author = {Marcjasz, Grzegorz and Narajewski, Micha{\l} and Weron, Rafa{\l} and Ziel, Florian},
|
||||
journal = {Energy Economics},
|
||||
volume = {125},
|
||||
pages = {106843},
|
||||
year = {2023},
|
||||
doi = {10.1016/j.eneco.2023.106843},
|
||||
publisher = {Elsevier}
|
||||
}
|
||||
@book{cesa2006prediction,
|
||||
title = {{Prediction, learning, and games}},
|
||||
author = {Cesa-Bianchi, Nicol{\`o} and Lugosi, G{\'a}bor},
|
||||
year = {2006},
|
||||
month = {3},
|
||||
publisher = {Cambridge university press},
|
||||
pages = {I--XII, 1--394},
|
||||
doi = {10.1017/CBO9780511546921},
|
||||
isbn = {978-0521841085}
|
||||
}
|
||||
@inproceedings{gaillard2018efficient,
|
||||
title = {{Efficient online algorithms for fast-rate regret bounds under sparsity}},
|
||||
author = {Gaillard, Pierre and Wintenberger, Olivier},
|
||||
year = {2018},
|
||||
month = {5},
|
||||
journal = {arXiv (Cornell University)},
|
||||
booktitle = {Proceedings of the 32nd International Conference on Neural Information Processing Systems},
|
||||
publisher = {Cornell University},
|
||||
pages = {7026--7036},
|
||||
doi = {10.48550/arxiv.1805.09174},
|
||||
url = {https://arxiv.org/abs/1805.09174},
|
||||
editor = {Bengio, Samy and Wallach, Hanna M. and Larochelle, Hugo and Grauman, Kristen and Cesa-Bianchi, Nicolò and Garnett, Roman}
|
||||
}
|
||||
@article{gneiting2007strictly,
|
||||
title = {{Strictly proper scoring rules, prediction, and estimation}},
|
||||
author = {Gneiting, Tilmann and Raftery, Adrian E},
|
||||
year = {2007},
|
||||
month = {3},
|
||||
journal = {Journal of the American statistical Association},
|
||||
publisher = {Taylor \& Francis},
|
||||
volume = {102},
|
||||
number = {477},
|
||||
pages = {359--378},
|
||||
doi = {10.1198/016214506000001437},
|
||||
issn = {0162-1459}
|
||||
}
|
||||
@article{gneiting2011making,
|
||||
title = {{Making and evaluating point forecasts}},
|
||||
author = {Gneiting, Tilmann},
|
||||
year = {2011},
|
||||
month = {6},
|
||||
journal = {Journal of the American Statistical Association},
|
||||
publisher = {Taylor \& Francis},
|
||||
volume = {106},
|
||||
number = {494},
|
||||
pages = {746--762},
|
||||
doi = {10.1198/jasa.2011.r10138},
|
||||
issn = {0162-1459},
|
||||
url = {https://arxiv.org/pdf/0912.0902.pdf}
|
||||
}
|
||||
@article{wintenberger2017optimal,
|
||||
title = {Optimal learning with Bernstein online aggregation},
|
||||
author = {Wintenberger, Olivier},
|
||||
year = {2017},
|
||||
journal = {Machine Learning},
|
||||
publisher = {Springer},
|
||||
volume = {106},
|
||||
number = {1},
|
||||
pages = {119--141},
|
||||
doi = {10.1007/s10994-016-5592-6}
|
||||
}
|
||||
@article{BERRISCH2023105221,
|
||||
title = {CRPS learning},
|
||||
author = {Jonathan Berrisch and Florian Ziel},
|
||||
year = {2023},
|
||||
month = {12},
|
||||
journal = {Journal of Econometrics},
|
||||
publisher = {Elsevier BV},
|
||||
volume = {237},
|
||||
number = {2, Part C},
|
||||
pages = {105221},
|
||||
doi = {10.1016/j.jeconom.2021.11.008},
|
||||
issn = {0304-4076},
|
||||
url = {https://arxiv.org/pdf/2102.00968},
|
||||
abstract = {Combination and aggregation techniques can significantly improve forecast accuracy. This also holds for probabilistic forecasting methods where predictive distributions are combined. There are several time-varying and adaptive weighting schemes such as Bayesian model averaging (BMA). However, the quality of different forecasts may vary not only over time but also within the distribution. For example, some distribution forecasts may be more accurate in the center of the distributions, while others are better at predicting the tails. Therefore, we introduce a new weighting method that considers the differences in performance over time and within the distribution. We discuss pointwise combination algorithms based on aggregation across quantiles that optimize with respect to the continuous ranked probability score (CRPS). After analyzing the theoretical properties of pointwise CRPS learning, we discuss B- and P-Spline-based estimation techniques for batch and online learning, based on quantile regression and prediction with expert advice. We prove that the proposed fully adaptive Bernstein online aggregation (BOA) method for pointwise CRPS online learning has optimal convergence properties. They are confirmed in simulations and a probabilistic forecasting study for European emission allowance (EUA) prices.},
|
||||
keywords = {Combination, Aggregation, Online, Probabilistic, Forecasting, Quantile, Time series, Distribution, Density, Prediction, Splines}
|
||||
}
|
||||
|
||||
@article{BERRISCH20241568,
|
||||
title = {Multivariate probabilistic CRPS learning with an application to day-ahead electricity prices},
|
||||
author = {Jonathan Berrisch and Florian Ziel},
|
||||
year = {2024},
|
||||
month = {10},
|
||||
journal = {International Journal of Forecasting},
|
||||
publisher = {Elsevier BV},
|
||||
volume = {40},
|
||||
number = {4},
|
||||
pages = {1568--1586},
|
||||
doi = {10.1016/j.ijforecast.2024.01.005},
|
||||
issn = {0169-2070},
|
||||
abstract = {This paper presents a new method for combining (or aggregating or ensembling) multivariate probabilistic forecasts, considering dependencies between quantiles and marginals through a smoothing procedure that allows for online learning. We discuss two smoothing methods: dimensionality reduction using Basis matrices and penalized smoothing. The new online learning algorithm generalizes the standard CRPS learning framework into multivariate dimensions. It is based on Bernstein Online Aggregation (BOA) and yields optimal asymptotic learning properties. The procedure uses horizontal aggregation, i.e., aggregation across quantiles. We provide an in-depth discussion on possible extensions of the algorithm and several nested cases related to the existing literature on online forecast combination. We apply the proposed methodology to forecasting day-ahead electricity prices, which are 24-dimensional distributional forecasts. The proposed method yields significant improvements over uniform combination in terms of continuous ranked probability score (CRPS). We discuss the temporal evolution of the weights and hyperparameters and present the results of reduced versions of the preferred model. A fast C++implementation of the proposed algorithm is provided in the open-source R-Package profoc on CRAN.},
|
||||
keywords = {Combination, Aggregation, Ensembling, Online, Multivariate, Probabilistic, Forecasting, Quantile, Time series, Distribution, Density, Prediction, Splines}
|
||||
}
|
||||
@article{berrisch2025rcpptimer,
|
||||
title = {rcpptimer: Rcpp Tic-Toc Timer with OpenMP Support},
|
||||
author = {Berrisch, Jonathan},
|
||||
year = {2025},
|
||||
month = {1},
|
||||
journal = {arXiv preprint arXiv:2501.15856},
|
||||
publisher = {Cornell University},
|
||||
volume = {abs/2501.15856},
|
||||
doi = {10.48550/arXiv.2501.15856},
|
||||
issn = {2331-8422},
|
||||
url = {https://arxiv.org/pdf/2501.15856}
|
||||
}
|
||||
@article{hirsch2024online,
|
||||
title = {Online Distributional Regression},
|
||||
author = {Hirsch, Simon and Berrisch, Jonathan and Ziel, Florian},
|
||||
year = {2024},
|
||||
month = {6},
|
||||
journal = {arXiv preprint arXiv:2407.08750},
|
||||
publisher = {Cornell University},
|
||||
volume = {abs/2407.08750},
|
||||
doi = {10.48550/arXiv.2407.08750},
|
||||
issn = {2331-8422},
|
||||
url = {https://arxiv.org/pdf/2407.08750}
|
||||
}
|
||||
@article{berrisch2022distributional,
|
||||
title = {Distributional modeling and forecasting of natural gas prices},
|
||||
author = {Berrisch, Jonathan and Ziel, Florian},
|
||||
year = {2022},
|
||||
month = {1},
|
||||
journal = {Journal of Forecasting},
|
||||
publisher = {Wiley},
|
||||
volume = {41},
|
||||
number = {6},
|
||||
pages = {1065--1086},
|
||||
doi = {10.1002/for.2853},
|
||||
issn = {0277-6693},
|
||||
url = {https://arxiv.org/pdf/2010.06227},
|
||||
abstract = {Abstract We examine the problem of modeling and forecasting European day-ahead and month-ahead natural gas prices. For this, we propose two distinct probabilistic models that can be utilized in risk and portfolio management. We use daily pricing data ranging from 2011 to 2020. Extensive descriptive data analysis shows that both time series feature heavy tails and conditional heteroscedasticity and show asymmetric behavior in their differences. We propose state-space time series models under skewed, heavy-tailed distributions to capture all stylized facts of the data. They include the impact of autocorrelation, seasonality, risk premia, temperature, storage levels, the price of European Emission Allowances, and related fuel prices of oil, coal, and electricity. We provide rigorous model diagnostics and interpret all model components in detail. Additionally, we conduct a probabilistic forecasting study with significance tests and compare the predictive performance against literature benchmarks. The proposed day-ahead (month-ahead) model leads to a 13\% (9\%) reduction in out-of-sample continuous ranked probability score (CRPS) compared with the best performing benchmark model, mainly due to adequate modeling of the volatility and heavy tails.},
|
||||
keywords = {gas prices, heavy-tailed distribution, probabilistic forecasting, risk premium, state-space models}
|
||||
}
|
||||
@article{BERRISCH2023100236,
|
||||
title = {High-resolution peak demand estimation using generalized additive models and deep neural networks},
|
||||
author = {Jonathan Berrisch and Micha{\l} Narajewski and Florian Ziel},
|
||||
year = {2023},
|
||||
month = {7},
|
||||
journal = {Energy and AI},
|
||||
publisher = {Elsevier BV},
|
||||
volume = {13},
|
||||
pages = {100236},
|
||||
doi = {10.1016/j.egyai.2023.100236},
|
||||
issn = {2666-5468},
|
||||
keywords = {Electricity peak load, Generalized additive models, Artificial neural networks, Prediction, Combination, Weather effects, Seasonality}
|
||||
}
|
||||
@book{johnson1995continuous,
|
||||
title = {Continuous univariate distributions, volume 2},
|
||||
author = {Johnson, Norman L and Kotz, Samuel and Balakrishnan, Narayanaswamy},
|
||||
year = {1995},
|
||||
publisher = {John wiley \& sons},
|
||||
volume = {289}
|
||||
}
|
||||
@article{li2022general,
|
||||
title = {General P-splines for non-uniform B-splines},
|
||||
author = {Li, Zheyuan and Cao, Jiguo},
|
||||
year = {2022},
|
||||
journal = {arXiv preprint},
|
||||
publisher = {Cornell University},
|
||||
doi = {10.48550/arXiv.2201.06808},
|
||||
url = {https://arxiv.org/abs/2201.06808}
|
||||
}
|
||||
@article{taylor2023angular,
|
||||
title = {Angular Combining of Forecasts of Probability Distributions},
|
||||
author = {Taylor, James W and Meng, Xiaochun},
|
||||
year = {2023},
|
||||
month = {5},
|
||||
journal = {arXiv preprint arXiv:2305.16735},
|
||||
publisher = {Cornell University},
|
||||
doi = {10.48550/arXiv.2305.16735},
|
||||
url = {https://arxiv.org/abs/2305.16735}
|
||||
}
|
||||
@@ -8,7 +8,7 @@ library(readr)
|
||||
# Creating faceted plots for different knot values and mu values
|
||||
# Create a function to generate the data for a given number of knots and mu value
|
||||
generate_basis_data <- function(num_knots, mu_value, sig_value, nonc_value, tailw_value, deg_value) {
|
||||
grid <- seq(from = 0.01, to = 0.99, length.out = 50)
|
||||
grid <- seq(from = 0, to = 1, length.out = 26)
|
||||
# Use provided degree
|
||||
B <- profoc:::make_basis_matrix(grid,
|
||||
profoc::make_knots(
|
||||
@@ -21,9 +21,9 @@ generate_basis_data <- function(num_knots, mu_value, sig_value, nonc_value, tail
|
||||
),
|
||||
deg = deg_value
|
||||
)
|
||||
B_mat <- round(as.matrix(B),2)
|
||||
B_mat <- round(as.matrix(B), 5)
|
||||
df <- as.data.frame(B_mat)
|
||||
df$x <- round(grid,2)
|
||||
df$x <- grid
|
||||
df_long <- pivot_longer(df,
|
||||
cols = -x,
|
||||
names_to = "b",
|
||||
@@ -39,10 +39,9 @@ generate_basis_data <- function(num_knots, mu_value, sig_value, nonc_value, tail
|
||||
}
|
||||
|
||||
# Generate data for each combination of knot, mu, sig, nonc, tailw, and deg
|
||||
knot_values <- c(10)
|
||||
mu_values <- seq(0.1, 0.9, by = 0.2)
|
||||
sig_values <- 2^(-2:2)
|
||||
nonc_values <- c(-4,-2,0,2,4)
|
||||
nonc_values <- c(-4, -2, 0, 2, 4)
|
||||
tailw_values <- 2^(-2:2)
|
||||
|
||||
# Create an empty list to store all combinations
|
||||
@@ -50,16 +49,13 @@ all_data <- list()
|
||||
counter <- 1
|
||||
|
||||
# Nested loops to cover all parameter combinations
|
||||
for (k in knot_values) {
|
||||
print(paste("Processing knots:", k))
|
||||
for (m in mu_values) {
|
||||
print(paste("Processing mu:", m))
|
||||
for (s in sig_values) {
|
||||
for (nc in nonc_values) {
|
||||
for (tw in tailw_values) {
|
||||
all_data[[counter]] <- generate_basis_data(5, m, s, nc, tw, 2)
|
||||
counter <- counter + 1
|
||||
}
|
||||
for (m in mu_values) {
|
||||
print(paste("Processing mu:", m))
|
||||
for (s in sig_values) {
|
||||
for (nc in nonc_values) {
|
||||
for (tw in tailw_values) {
|
||||
all_data[[counter]] <- generate_basis_data(5, m, s, nc, tw, 2)
|
||||
counter <- counter + 1
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -68,4 +64,19 @@ for (k in knot_values) {
|
||||
# Combine all data frames
|
||||
all_data <- bind_rows(all_data)
|
||||
|
||||
write_csv(all_data, "basis_functions.csv")
|
||||
write_csv(all_data, "25_07_phd_defense/assets/mcrps_learning/basis_functions.csv")
|
||||
|
||||
# %%
|
||||
all_data %>%
|
||||
filter(mu == 0.1) %>%
|
||||
filter(sig == 0.25) %>%
|
||||
filter(nonc == -4) %>%
|
||||
filter(tailw == 0.25) %>%
|
||||
ggplot(aes(x = x, y = y, col = b)) +
|
||||
geom_line(size = 2) +
|
||||
labs(
|
||||
title = "Basis Functions for Different Knot Values",
|
||||
x = "x",
|
||||
y = "y"
|
||||
) +
|
||||
theme_minimal()
|
||||
809
assets/mcrps_learning/algorithm.svg
Normal file
@@ -0,0 +1,809 @@
|
||||
<svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" version="1.1" width="369.75846pt" height="380.82173pt" viewBox="0 0 369.75846 380.82173">
|
||||
<defs>
|
||||
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<use data-text="." xlink:href="#font_3_3" transform="matrix(9.96264,0,0,-9.96264,83.340419,334.74827)"/>
|
||||
<use data-text="." xlink:href="#font_3_3" transform="matrix(9.96264,0,0,-9.96264,87.76382,334.74827)"/>
|
||||
<use data-text="," xlink:href="#font_3_4" transform="matrix(9.96264,0,0,-9.96264,92.19718,334.74827)"/>
|
||||
<use data-text="K" xlink:href="#font_3_8" transform="matrix(9.96264,0,0,-9.96264,96.63055,334.74827)"/>
|
||||
<use data-text="d" xlink:href="#font_0_47" transform="matrix(9.96264,0,0,-9.96264,109.11364,334.74827)"/>
|
||||
<use data-text="o" xlink:href="#font_0_81" transform="matrix(9.96264,0,0,-9.96264,115.479778,334.74827)"/>
|
||||
<path transform="matrix(1,0,0,-1,36.12664,358.06028)" stroke-width=".398" stroke-linecap="butt" stroke-miterlimit="10" stroke-linejoin="miter" fill="none" stroke="#000000" d="M0 0V17.933"/>
|
||||
<use data-text="1" xlink:href="#font_2_82" transform="matrix(6.97385,0,0,-6.97385,2.3946458,352.68028)"/>
|
||||
<use data-text="7" xlink:href="#font_2_100" transform="matrix(6.97385,0,0,-6.97385,6.906723,352.68028)"/>
|
||||
<use data-text="w" xlink:href="#font_8_9" transform="matrix(9.96264,0,0,-9.96264,46.288644,352.68028)"/>
|
||||
<use data-text="t" xlink:href="#font_7_10" transform="matrix(6.97385,0,0,-6.97385,54.571649,354.17527)"/>
|
||||
<use data-text="," xlink:href="#font_7_4" transform="matrix(6.97385,0,0,-6.97385,57.58436,354.17527)"/>
|
||||
<use data-text="k" xlink:href="#font_7_8" transform="matrix(6.97385,0,0,-6.97385,59.948495,354.17527)"/>
|
||||
<use data-text="(" xlink:href="#font_5_1" transform="matrix(9.96264,0,0,-9.96264,64.84965,352.68028)"/>
|
||||
<use data-text="P" xlink:href="#font_20_2" transform="matrix(9.96264,0,0,-9.96264,68.72364,352.68028)"/>
|
||||
<use data-text=")" xlink:href="#font_5_2" transform="matrix(9.96264,0,0,-9.96264,77.634639,352.68028)"/>
|
||||
<use data-text="=" xlink:href="#font_5_6" transform="matrix(9.96264,0,0,-9.96264,84.26977,352.68028)"/>
|
||||
<use data-text="H" xlink:href="#font_20_1" transform="matrix(9.96264,0,0,-9.96264,94.79264,352.68028)"/>
|
||||
<use data-text="m" xlink:href="#font_11_75" transform="matrix(6.97385,0,0,-6.97385,104.62965,348.3083)"/>
|
||||
<use data-text="v" xlink:href="#font_11_112" transform="matrix(6.97385,0,0,-6.97385,110.96191,348.3083)"/>
|
||||
<use data-text="B" xlink:href="#font_8_3" transform="matrix(9.96264,0,0,-9.96264,115.644649,352.68028)"/>
|
||||
<use data-text="m" xlink:href="#font_11_75" transform="matrix(6.97385,0,0,-6.97385,124.75764,349.06529)"/>
|
||||
<use data-text="v" xlink:href="#font_11_112" transform="matrix(6.97385,0,0,-6.97385,131.0899,349.06529)"/>
|
||||
<use data-text="β" xlink:href="#font_8_1" transform="matrix(9.96264,0,0,-9.96264,135.77265,352.68028)"/>
|
||||
<use data-text="t" xlink:href="#font_7_10" transform="matrix(6.97385,0,0,-6.97385,142.34464,354.17527)"/>
|
||||
<use data-text="," xlink:href="#font_7_4" transform="matrix(6.97385,0,0,-6.97385,145.35736,354.17527)"/>
|
||||
<use data-text="k" xlink:href="#font_7_8" transform="matrix(6.97385,0,0,-6.97385,147.7215,354.17527)"/>
|
||||
<use data-text="B" xlink:href="#font_8_3" transform="matrix(9.96264,0,0,-9.96264,152.62265,352.68028)"/>
|
||||
<use data-text="p" xlink:href="#font_11_84" transform="matrix(6.97385,0,0,-6.97385,161.73566,349.06529)"/>
|
||||
<use data-text="r" xlink:href="#font_11_96" transform="matrix(6.97385,0,0,-6.97385,166.13617,349.06529)"/>
|
||||
<use data-text="′" xlink:href="#font_9_3" transform="matrix(6.97385,0,0,-6.97385,169.74466,348.3083)"/>
|
||||
<use data-text="H" xlink:href="#font_20_1" transform="matrix(9.96264,0,0,-9.96264,172.53964,352.68028)"/>
|
||||
<use data-text="p" xlink:href="#font_11_84" transform="matrix(6.97385,0,0,-6.97385,182.37665,348.3083)"/>
|
||||
<use data-text="r" xlink:href="#font_11_96" transform="matrix(6.97385,0,0,-6.97385,186.77716,348.3083)"/>
|
||||
<use data-text="1" xlink:href="#font_2_82" transform="matrix(6.97385,0,0,-6.97385,1.597641,371.60929)"/>
|
||||
<use data-text="8" xlink:href="#font_2_51" transform="matrix(6.97385,0,0,-6.97385,6.1097185,371.60929)"/>
|
||||
<use data-text="e" xlink:href="#font_0_50" transform="matrix(9.96264,0,0,-9.96264,15.603645,371.60929)"/>
|
||||
<use data-text="n" xlink:href="#font_0_77" transform="matrix(9.96264,0,0,-9.96264,20.85395,371.60929)"/>
|
||||
<use data-text="d" xlink:href="#font_0_47" transform="matrix(9.96264,0,0,-9.96264,27.220086,371.60929)"/>
|
||||
<path transform="matrix(1,0,0,-1,.6596451,379.38029)" stroke-width=".797" stroke-linecap="butt" stroke-miterlimit="10" stroke-linejoin="miter" fill="none" stroke="#000000" d="M0 0H368.504"/>
|
||||
<use data-text="1" xlink:href="#font_1_82" transform="matrix(9.96264,0,0,-9.96264,182.42066,642.9203)"/>
|
||||
</svg>
|
||||
|
After Width: | Height: | Size: 216 KiB |
1282
assets/mcrps_learning/constant.svg
Normal file
|
After Width: | Height: | Size: 95 KiB |
2575
assets/mcrps_learning/constant_mv.svg
Normal file
|
After Width: | Height: | Size: 177 KiB |
2270
assets/mcrps_learning/constant_pr.svg
Normal file
|
After Width: | Height: | Size: 158 KiB |
983
assets/mcrps_learning/knot_placement.svg
Normal file
|
After Width: | Height: | Size: 1.7 MiB |
@@ -1,15 +1,15 @@
|
||||
---
|
||||
title: "Data Science Methods for Forecasting in Energy and Economics"
|
||||
title: "Knots-Demo"
|
||||
date: 2025-07-10
|
||||
format:
|
||||
revealjs:
|
||||
embed-resources: true
|
||||
footer: ""
|
||||
execute:
|
||||
daemon: false
|
||||
highlight-style: github
|
||||
---
|
||||
|
||||
|
||||
```{ojs}
|
||||
d3 = require("d3@7")
|
||||
```
|
||||
@@ -86,9 +86,31 @@ chart = {
|
||||
.style('width', '100%');
|
||||
sliderCont.append('span').text(d => (d.label.match(/Sigma|Tailweight/) ? d.get() : d.get()))
|
||||
.style('font-size','20px');
|
||||
// Build SVG
|
||||
const width = 800;
|
||||
const height = 400;
|
||||
|
||||
// Add Reset button to clear all sliders to their defaults
|
||||
controlsContainer.append('button')
|
||||
.text('Reset')
|
||||
.style('font-size', '20px')
|
||||
.style('align-self', 'center')
|
||||
.style('margin-left', 'auto')
|
||||
.on('click', () => {
|
||||
// reset state vars
|
||||
selectedMu = 0.5;
|
||||
selectedSig = 1;
|
||||
selectedNonc = 0;
|
||||
selectedTailw = 1;
|
||||
// update input positions
|
||||
sliderCont.selectAll('input').property('value', d => d.get());
|
||||
// update displayed labels
|
||||
sliderCont.selectAll('span')
|
||||
.text(d => d.label.match(/Sigma|Tailweight/) ? (2**d.get()) : d.get());
|
||||
// redraw chart
|
||||
updateChart(filteredData());
|
||||
});
|
||||
|
||||
// Build SVG
|
||||
const width = 1200;
|
||||
const height = 450;
|
||||
const margin = {top: 40, right: 20, bottom: 40, left: 40};
|
||||
const innerWidth = width - margin.left - margin.right;
|
||||
const innerHeight = height - margin.top - margin.bottom;
|
||||
@@ -105,7 +127,7 @@ chart = {
|
||||
.range([0, innerWidth]);
|
||||
|
||||
const y = d3.scaleLinear()
|
||||
.domain([0, 0.7])
|
||||
.domain([0, 1])
|
||||
.range([innerHeight, 0]);
|
||||
|
||||
// Create a color scale for the basis functions
|
||||
@@ -119,15 +141,6 @@ chart = {
|
||||
.attr("preserveAspectRatio", "xMidYMid meet")
|
||||
.attr("style", "max-width: 100%; height: auto;");
|
||||
|
||||
// Add chart title
|
||||
// svg.append("text")
|
||||
// .attr("class", "chart-title")
|
||||
// .attr("x", width / 2)
|
||||
// .attr("y", 20)
|
||||
// .attr("text-anchor", "middle")
|
||||
// .attr("font-size", "20px")
|
||||
// .attr("font-weight", "bold");
|
||||
|
||||
// Create the chart group
|
||||
const g = svg.append("g")
|
||||
.attr("transform", `translate(${margin.left},${margin.top})`);
|
||||
@@ -144,20 +157,6 @@ chart = {
|
||||
.call(d3.axisLeft(y).ticks(5))
|
||||
.style("font-size", "20px");
|
||||
|
||||
// Add axis labels
|
||||
// g.append("text")
|
||||
// .attr("x", innerWidth / 2)
|
||||
// .attr("y", innerHeight + 35)
|
||||
// .attr("text-anchor", "middle")
|
||||
// .text("x");
|
||||
|
||||
// g.append("text")
|
||||
// .attr("transform", "rotate(-90)")
|
||||
// .attr("x", -innerHeight / 2)
|
||||
// .attr("y", -30)
|
||||
// .attr("text-anchor", "middle")
|
||||
// .text("y");
|
||||
|
||||
// Add a horizontal line at y = 0
|
||||
g.append("line")
|
||||
.attr("x1", 0)
|
||||
@@ -207,4 +206,4 @@ chart = {
|
||||
container.node().appendChild(svg.node());
|
||||
return container.node();
|
||||
}
|
||||
```
|
||||
```
|
||||
5103
assets/mcrps_learning/pointwise.svg
Normal file
|
After Width: | Height: | Size: 337 KiB |
BIN
assets/mcrps_learning/profoc_langs.png
Normal file
|
After Width: | Height: | Size: 25 KiB |
3476
assets/mcrps_learning/smooth_best.svg
Normal file
|
After Width: | Height: | Size: 234 KiB |
BIN
assets/mcrps_learning/web_pres.png
Normal file
|
After Width: | Height: | Size: 1.9 KiB |
1105
assets/ondir/ondir_flow.excalidraw
Normal file
4
assets/ondir/ondir_flow.svg
Normal file
|
After Width: | Height: | Size: 29 KiB |
687
assets/revealjs/apa-old-doi-prefix.csl
Normal file
@@ -0,0 +1,687 @@
|
||||
<?xml version="1.0" encoding="utf-8"?>
|
||||
<style xmlns="http://purl.org/net/xbiblio/csl" class="in-text" version="1.0" demote-non-dropping-particle="never">
|
||||
<info>
|
||||
<title>American Psychological Association 6th edition ("DOI:" DOI prefix)</title>
|
||||
<title-short>APA</title-short>
|
||||
<id>http://www.zotero.org/styles/apa-old-doi-prefix</id>
|
||||
<link href="http://www.zotero.org/styles/apa-old-doi-prefix" rel="self"/>
|
||||
<link href="http://owl.english.purdue.edu/owl/resource/560/01/" rel="documentation"/>
|
||||
<author>
|
||||
<name>Simon Kornblith</name>
|
||||
<email>simon@simonster.com</email>
|
||||
</author>
|
||||
<contributor>
|
||||
<name>Bruce D'Arcus</name>
|
||||
</contributor>
|
||||
<contributor>
|
||||
<name>Curtis M. Humphrey</name>
|
||||
</contributor>
|
||||
<contributor>
|
||||
<name>Richard Karnesky</name>
|
||||
<email>karnesky+zotero@gmail.com</email>
|
||||
<uri>http://arc.nucapt.northwestern.edu/Richard_Karnesky</uri>
|
||||
</contributor>
|
||||
<contributor>
|
||||
<name>Sebastian Karcher</name>
|
||||
</contributor>
|
||||
<contributor>
|
||||
<name> Brenton M. Wiernik</name>
|
||||
<email>zotero@wiernik.org</email>
|
||||
</contributor>
|
||||
<category citation-format="author-date"/>
|
||||
<category field="psychology"/>
|
||||
<category field="generic-base"/>
|
||||
<updated>2017-09-05T01:06:39+00:00</updated>
|
||||
<rights license="http://creativecommons.org/licenses/by-sa/3.0/">This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 License</rights>
|
||||
</info>
|
||||
<locale xml:lang="en">
|
||||
<terms>
|
||||
<term name="editortranslator" form="short">
|
||||
<single>ed. & trans.</single>
|
||||
<multiple>eds. & trans.</multiple>
|
||||
</term>
|
||||
<term name="translator" form="short">
|
||||
<single>trans.</single>
|
||||
<multiple>trans.</multiple>
|
||||
</term>
|
||||
</terms>
|
||||
</locale>
|
||||
<macro name="container-contributors">
|
||||
<choose>
|
||||
<if type="chapter paper-conference entry-dictionary entry-encyclopedia" match="any">
|
||||
<group delimiter=", ">
|
||||
<names variable="container-author" delimiter=", ">
|
||||
<name and="symbol" initialize-with=". " delimiter=", "/>
|
||||
<label form="short" prefix=" (" text-case="title" suffix=")"/>
|
||||
</names>
|
||||
<names variable="editor translator" delimiter=", ">
|
||||
<name and="symbol" initialize-with=". " delimiter=", "/>
|
||||
<label form="short" prefix=" (" text-case="title" suffix=")"/>
|
||||
</names>
|
||||
</group>
|
||||
</if>
|
||||
</choose>
|
||||
</macro>
|
||||
<macro name="secondary-contributors">
|
||||
<choose>
|
||||
<if type="article-journal chapter paper-conference entry-dictionary entry-encyclopedia" match="none">
|
||||
<group delimiter=", " prefix=" (" suffix=")">
|
||||
<names variable="container-author" delimiter=", ">
|
||||
<name and="symbol" initialize-with=". " delimiter=", "/>
|
||||
<label form="short" prefix=", " text-case="title"/>
|
||||
</names>
|
||||
<names variable="editor translator" delimiter=", ">
|
||||
<name and="symbol" initialize-with=". " delimiter=", "/>
|
||||
<label form="short" prefix=", " text-case="title"/>
|
||||
</names>
|
||||
</group>
|
||||
</if>
|
||||
</choose>
|
||||
</macro>
|
||||
<macro name="author">
|
||||
<names variable="author">
|
||||
<name name-as-sort-order="all" and="symbol" sort-separator=", " initialize-with="." delimiter=", " delimiter-precedes-last="always"/>
|
||||
<label form="short" prefix=" (" suffix=")" text-case="capitalize-first"/>
|
||||
<substitute>
|
||||
<names variable="editor"/>
|
||||
<names variable="translator"/>
|
||||
<choose>
|
||||
<if type="report">
|
||||
<text variable="publisher"/>
|
||||
<text macro="title"/>
|
||||
</if>
|
||||
<else>
|
||||
<text macro="title"/>
|
||||
</else>
|
||||
</choose>
|
||||
</substitute>
|
||||
</names>
|
||||
</macro>
|
||||
<macro name="author-short">
|
||||
<choose>
|
||||
<if type="patent" variable="number" match="all">
|
||||
<text macro="patent-number"/>
|
||||
</if>
|
||||
<else>
|
||||
<names variable="author">
|
||||
<name form="short" and="symbol" delimiter=", " initialize-with=". "/>
|
||||
<substitute>
|
||||
<names variable="editor"/>
|
||||
<names variable="translator"/>
|
||||
<choose>
|
||||
<if type="report">
|
||||
<text variable="publisher"/>
|
||||
<text variable="title" form="short" font-style="italic"/>
|
||||
</if>
|
||||
<else-if type="legal_case">
|
||||
<text variable="title" font-style="italic"/>
|
||||
</else-if>
|
||||
<else-if type="book graphic motion_picture song" match="any">
|
||||
<text variable="title" form="short" font-style="italic"/>
|
||||
</else-if>
|
||||
<else-if type="bill legislation" match="any">
|
||||
<text variable="title" form="short"/>
|
||||
</else-if>
|
||||
<else-if variable="reviewed-author">
|
||||
<choose>
|
||||
<if variable="reviewed-title" match="none">
|
||||
<text variable="title" form="short" font-style="italic" prefix="Review of "/>
|
||||
</if>
|
||||
<else>
|
||||
<text variable="title" form="short" quotes="true"/>
|
||||
</else>
|
||||
</choose>
|
||||
</else-if>
|
||||
<else>
|
||||
<text variable="title" form="short" quotes="true"/>
|
||||
</else>
|
||||
</choose>
|
||||
</substitute>
|
||||
</names>
|
||||
</else>
|
||||
</choose>
|
||||
</macro>
|
||||
<macro name="patent-number">
|
||||
<!-- genre: U.S. Patent number: 123,445-->
|
||||
<group delimiter=" ">
|
||||
<group delimiter=" ">
|
||||
<text variable="genre"/>
|
||||
<text term="issue" form="short" text-case="capitalize-first"/>
|
||||
</group>
|
||||
<text variable="number"/>
|
||||
</group>
|
||||
</macro>
|
||||
<macro name="access">
|
||||
<choose>
|
||||
<if type="thesis report" match="any">
|
||||
<choose>
|
||||
<if variable="DOI" match="any">
|
||||
<text variable="DOI" prefix="DOI: /"/>
|
||||
</if>
|
||||
<else-if variable="URL" match="any">
|
||||
<group>
|
||||
<text variable="URL"/>
|
||||
</group>
|
||||
</else-if>
|
||||
<else-if variable="archive" match="any">
|
||||
<group>
|
||||
<text term="retrieved" text-case="capitalize-first" suffix=" "/>
|
||||
<text term="from" suffix=" "/>
|
||||
<text variable="archive" suffix="."/>
|
||||
<text variable="archive_location" prefix=" (" suffix=")"/>
|
||||
</group>
|
||||
</else-if>
|
||||
</choose>
|
||||
</if>
|
||||
<else>
|
||||
<choose>
|
||||
<if variable="DOI">
|
||||
<text variable="DOI" prefix="DOI: "/>
|
||||
</if>
|
||||
<else>
|
||||
<choose>
|
||||
<if type="post post-weblog webpage" match="any">
|
||||
<group delimiter=" ">
|
||||
<text term="retrieved" text-case="capitalize-first" suffix=" "/>
|
||||
<group>
|
||||
<date variable="accessed" form="text" suffix=", "/>
|
||||
</group>
|
||||
<text term="from"/>
|
||||
<text variable="URL"/>
|
||||
</group>
|
||||
</if>
|
||||
<else>
|
||||
<group>
|
||||
<text variable="URL"/>
|
||||
</group>
|
||||
</else>
|
||||
</choose>
|
||||
</else>
|
||||
</choose>
|
||||
</else>
|
||||
</choose>
|
||||
</macro>
|
||||
<macro name="title">
|
||||
<choose>
|
||||
<if type="book graphic manuscript motion_picture report song speech thesis" match="any">
|
||||
<choose>
|
||||
<if variable="version" type="book" match="all">
|
||||
<!---This is a hack until we have a computer program type -->
|
||||
<text variable="title"/>
|
||||
</if>
|
||||
<else>
|
||||
<text variable="title" font-style="italic"/>
|
||||
</else>
|
||||
</choose>
|
||||
</if>
|
||||
<else-if variable="reviewed-author">
|
||||
<choose>
|
||||
<if variable="reviewed-title">
|
||||
<group delimiter=" ">
|
||||
<text variable="title"/>
|
||||
<group delimiter=", " prefix="[" suffix="]">
|
||||
<text variable="reviewed-title" font-style="italic" prefix="Review of "/>
|
||||
<names variable="reviewed-author" delimiter=", ">
|
||||
<label form="verb-short" suffix=" "/>
|
||||
<name and="symbol" initialize-with=". " delimiter=", "/>
|
||||
</names>
|
||||
</group>
|
||||
</group>
|
||||
</if>
|
||||
<else>
|
||||
<!-- assume `title` is title of reviewed work -->
|
||||
<group delimiter=", " prefix="[" suffix="]">
|
||||
<text variable="title" font-style="italic" prefix="Review of "/>
|
||||
<names variable="reviewed-author" delimiter=", ">
|
||||
<label form="verb-short" suffix=" "/>
|
||||
<name and="symbol" initialize-with=". " delimiter=", "/>
|
||||
</names>
|
||||
</group>
|
||||
</else>
|
||||
</choose>
|
||||
</else-if>
|
||||
<else-if type="patent" variable="number" match="all">
|
||||
<text macro="patent-number" font-style="italic"/>
|
||||
</else-if>
|
||||
<else>
|
||||
<text variable="title"/>
|
||||
</else>
|
||||
</choose>
|
||||
</macro>
|
||||
<macro name="title-plus-extra">
|
||||
<text macro="title"/>
|
||||
<choose>
|
||||
<if type="report thesis" match="any">
|
||||
<group prefix=" (" suffix=")" delimiter=", ">
|
||||
<group delimiter=" ">
|
||||
<choose>
|
||||
<if variable="genre" match="any">
|
||||
<text variable="genre"/>
|
||||
</if>
|
||||
<else>
|
||||
<text variable="collection-title"/>
|
||||
</else>
|
||||
</choose>
|
||||
<text variable="number" prefix="No. "/>
|
||||
</group>
|
||||
<group delimiter=" ">
|
||||
<text term="version" text-case="capitalize-first"/>
|
||||
<text variable="version"/>
|
||||
</group>
|
||||
<text macro="edition"/>
|
||||
</group>
|
||||
</if>
|
||||
<else-if type="post-weblog webpage" match="any">
|
||||
<text variable="genre" prefix=" [" suffix="]"/>
|
||||
</else-if>
|
||||
<else-if variable="version">
|
||||
<group delimiter=" " prefix=" (" suffix=")">
|
||||
<text term="version" text-case="capitalize-first"/>
|
||||
<text variable="version"/>
|
||||
</group>
|
||||
</else-if>
|
||||
</choose>
|
||||
<text macro="format" prefix=" [" suffix="]"/>
|
||||
</macro>
|
||||
<macro name="format">
|
||||
<choose>
|
||||
<if match="any" variable="medium">
|
||||
<text variable="medium" text-case="capitalize-first"/>
|
||||
</if>
|
||||
<else-if type="dataset" match="any">
|
||||
<text value="Data set"/>
|
||||
</else-if>
|
||||
</choose>
|
||||
</macro>
|
||||
<macro name="publisher">
|
||||
<choose>
|
||||
<if type="report" match="any">
|
||||
<group delimiter=": ">
|
||||
<text variable="publisher-place"/>
|
||||
<text variable="publisher"/>
|
||||
</group>
|
||||
</if>
|
||||
<else-if type="thesis" match="any">
|
||||
<group delimiter=", ">
|
||||
<text variable="publisher"/>
|
||||
<text variable="publisher-place"/>
|
||||
</group>
|
||||
</else-if>
|
||||
<else-if type="patent">
|
||||
<group delimiter=": ">
|
||||
<text variable="publisher-place"/>
|
||||
<choose>
|
||||
<if variable="publisher">
|
||||
<text variable="publisher"/>
|
||||
</if>
|
||||
<else>
|
||||
<text variable="authority"/>
|
||||
</else>
|
||||
</choose>
|
||||
</group>
|
||||
</else-if>
|
||||
<else-if type="post-weblog webpage" match="none">
|
||||
<group delimiter=", ">
|
||||
<choose>
|
||||
<if variable="event version" type="speech motion_picture" match="none">
|
||||
<!-- Including version is to avoid printing the programming language for computerProgram /-->
|
||||
<text variable="genre"/>
|
||||
</if>
|
||||
</choose>
|
||||
<choose>
|
||||
<if type="article-journal article-magazine article-newspaper" match="none">
|
||||
<group delimiter=": ">
|
||||
<choose>
|
||||
<if variable="publisher-place">
|
||||
<text variable="publisher-place"/>
|
||||
</if>
|
||||
<else>
|
||||
<text variable="event-place"/>
|
||||
</else>
|
||||
</choose>
|
||||
<text variable="publisher"/>
|
||||
</group>
|
||||
</if>
|
||||
</choose>
|
||||
</group>
|
||||
</else-if>
|
||||
</choose>
|
||||
</macro>
|
||||
<macro name="event">
|
||||
<choose>
|
||||
<if variable="container-title" match="none">
|
||||
<choose>
|
||||
<if variable="event">
|
||||
<choose>
|
||||
<if variable="genre" match="none">
|
||||
<text term="presented at" text-case="capitalize-first" suffix=" "/>
|
||||
<text variable="event"/>
|
||||
</if>
|
||||
<else>
|
||||
<group delimiter=" ">
|
||||
<text variable="genre" text-case="capitalize-first"/>
|
||||
<text term="presented at"/>
|
||||
<text variable="event"/>
|
||||
</group>
|
||||
</else>
|
||||
</choose>
|
||||
</if>
|
||||
<else-if type="speech">
|
||||
<text variable="genre" text-case="capitalize-first"/>
|
||||
</else-if>
|
||||
</choose>
|
||||
</if>
|
||||
</choose>
|
||||
</macro>
|
||||
<macro name="issued">
|
||||
<choose>
|
||||
<if type="bill legal_case legislation" match="none">
|
||||
<choose>
|
||||
<if variable="issued">
|
||||
<group prefix=" (" suffix=")">
|
||||
<date variable="issued">
|
||||
<date-part name="year"/>
|
||||
</date>
|
||||
<text variable="year-suffix"/>
|
||||
<choose>
|
||||
<if type="speech" match="any">
|
||||
<date variable="issued">
|
||||
<date-part prefix=", " name="month"/>
|
||||
</date>
|
||||
</if>
|
||||
<else-if type="article-journal bill book chapter graphic legal_case legislation motion_picture paper-conference report song dataset" match="none">
|
||||
<date variable="issued">
|
||||
<date-part prefix=", " name="month"/>
|
||||
<date-part prefix=" " name="day"/>
|
||||
</date>
|
||||
</else-if>
|
||||
</choose>
|
||||
</group>
|
||||
</if>
|
||||
<else-if variable="status">
|
||||
<group prefix=" (" suffix=")">
|
||||
<text variable="status"/>
|
||||
<text variable="year-suffix" prefix="-"/>
|
||||
</group>
|
||||
</else-if>
|
||||
<else>
|
||||
<group prefix=" (" suffix=")">
|
||||
<text term="no date" form="short"/>
|
||||
<text variable="year-suffix" prefix="-"/>
|
||||
</group>
|
||||
</else>
|
||||
</choose>
|
||||
</if>
|
||||
</choose>
|
||||
</macro>
|
||||
<macro name="issued-sort">
|
||||
<choose>
|
||||
<if type="article-journal bill book chapter graphic legal_case legislation motion_picture paper-conference report song dataset" match="none">
|
||||
<date variable="issued">
|
||||
<date-part name="year"/>
|
||||
<date-part name="month"/>
|
||||
<date-part name="day"/>
|
||||
</date>
|
||||
</if>
|
||||
<else>
|
||||
<date variable="issued">
|
||||
<date-part name="year"/>
|
||||
</date>
|
||||
</else>
|
||||
</choose>
|
||||
</macro>
|
||||
<macro name="issued-year">
|
||||
<choose>
|
||||
<if variable="issued">
|
||||
<group delimiter="/">
|
||||
<date variable="original-date" form="text"/>
|
||||
<group>
|
||||
<date variable="issued">
|
||||
<date-part name="year"/>
|
||||
</date>
|
||||
<text variable="year-suffix"/>
|
||||
</group>
|
||||
</group>
|
||||
</if>
|
||||
<else-if variable="status">
|
||||
<text variable="status"/>
|
||||
<text variable="year-suffix" prefix="-"/>
|
||||
</else-if>
|
||||
<else>
|
||||
<text term="no date" form="short"/>
|
||||
<text variable="year-suffix" prefix="-"/>
|
||||
</else>
|
||||
</choose>
|
||||
</macro>
|
||||
<macro name="edition">
|
||||
<choose>
|
||||
<if is-numeric="edition">
|
||||
<group delimiter=" ">
|
||||
<number variable="edition" form="ordinal"/>
|
||||
<text term="edition" form="short"/>
|
||||
</group>
|
||||
</if>
|
||||
<else>
|
||||
<text variable="edition"/>
|
||||
</else>
|
||||
</choose>
|
||||
</macro>
|
||||
<macro name="locators">
|
||||
<choose>
|
||||
<if type="article-journal article-magazine" match="any">
|
||||
<group prefix=", " delimiter=", ">
|
||||
<group>
|
||||
<text variable="volume" font-style="bold"/>
|
||||
<text variable="issue" prefix="(" suffix=")"/>
|
||||
</group>
|
||||
<text variable="page"/>
|
||||
</group>
|
||||
<choose>
|
||||
<!--for advanced online publication-->
|
||||
<if variable="issued">
|
||||
<choose>
|
||||
<if variable="page issue" match="none">
|
||||
<text variable="status" prefix=". "/>
|
||||
</if>
|
||||
</choose>
|
||||
</if>
|
||||
</choose>
|
||||
</if>
|
||||
<else-if type="article-newspaper">
|
||||
<group delimiter=" " prefix=", ">
|
||||
<label variable="page" form="short"/>
|
||||
<text variable="page"/>
|
||||
</group>
|
||||
</else-if>
|
||||
<else-if type="book graphic motion_picture report song chapter paper-conference entry-encyclopedia entry-dictionary" match="any">
|
||||
<group prefix=" (" suffix=")" delimiter=", ">
|
||||
<choose>
|
||||
<if type="report" match="none">
|
||||
<!-- edition for report is included in title-plus-extra /-->
|
||||
<text macro="edition"/>
|
||||
</if>
|
||||
</choose>
|
||||
<choose>
|
||||
<if variable="volume" match="any">
|
||||
<group>
|
||||
<text term="volume" form="short" text-case="capitalize-first" suffix=" "/>
|
||||
<number variable="volume" form="numeric"/>
|
||||
</group>
|
||||
</if>
|
||||
<else>
|
||||
<group>
|
||||
<text term="volume" form="short" plural="true" text-case="capitalize-first" suffix=" "/>
|
||||
<number variable="number-of-volumes" form="numeric" prefix="1–"/>
|
||||
</group>
|
||||
</else>
|
||||
</choose>
|
||||
<group>
|
||||
<label variable="page" form="short" suffix=" "/>
|
||||
<text variable="page"/>
|
||||
</group>
|
||||
</group>
|
||||
</else-if>
|
||||
<else-if type="legal_case">
|
||||
<group prefix=" (" suffix=")" delimiter=" ">
|
||||
<text variable="authority"/>
|
||||
<choose>
|
||||
<if variable="container-title" match="any">
|
||||
<!--Only print year for cases published in reporters-->
|
||||
<date variable="issued" form="numeric" date-parts="year"/>
|
||||
</if>
|
||||
<else>
|
||||
<date variable="issued" form="text"/>
|
||||
</else>
|
||||
</choose>
|
||||
</group>
|
||||
</else-if>
|
||||
<else-if type="bill legislation" match="any">
|
||||
<date variable="issued" prefix=" (" suffix=")">
|
||||
<date-part name="year"/>
|
||||
</date>
|
||||
</else-if>
|
||||
</choose>
|
||||
</macro>
|
||||
<macro name="citation-locator">
|
||||
<group>
|
||||
<choose>
|
||||
<if locator="chapter">
|
||||
<label variable="locator" form="long" text-case="capitalize-first"/>
|
||||
</if>
|
||||
<else>
|
||||
<label variable="locator" form="short"/>
|
||||
</else>
|
||||
</choose>
|
||||
<text variable="locator" prefix=" "/>
|
||||
</group>
|
||||
</macro>
|
||||
<macro name="container">
|
||||
<choose>
|
||||
<if type="post-weblog webpage" match="none">
|
||||
<group>
|
||||
<choose>
|
||||
<if type="chapter paper-conference entry-encyclopedia" match="any">
|
||||
<text term="in" text-case="capitalize-first" suffix=" "/>
|
||||
</if>
|
||||
</choose>
|
||||
<group delimiter=", ">
|
||||
<text macro="container-contributors"/>
|
||||
<text macro="secondary-contributors"/>
|
||||
<text macro="container-title"/>
|
||||
</group>
|
||||
</group>
|
||||
</if>
|
||||
</choose>
|
||||
</macro>
|
||||
<macro name="container-title">
|
||||
<choose>
|
||||
<if type="article article-journal article-magazine article-newspaper" match="any">
|
||||
<text variable="container-title" font-style="italic" text-case="title"/>
|
||||
</if>
|
||||
<else-if type="bill legal_case legislation" match="none">
|
||||
<text variable="container-title" font-style="italic"/>
|
||||
</else-if>
|
||||
</choose>
|
||||
</macro>
|
||||
<macro name="legal-cites">
|
||||
<choose>
|
||||
<if type="legal_case" match="any">
|
||||
<group prefix=", " delimiter=" ">
|
||||
<choose>
|
||||
<if variable="container-title">
|
||||
<text variable="volume"/>
|
||||
<text variable="container-title"/>
|
||||
<group delimiter=" ">
|
||||
<!--change to label variable="section" as that becomes available -->
|
||||
<text term="section" form="symbol"/>
|
||||
<text variable="section"/>
|
||||
</group>
|
||||
<text variable="page"/>
|
||||
</if>
|
||||
<else>
|
||||
<text variable="number" prefix="No. "/>
|
||||
</else>
|
||||
</choose>
|
||||
</group>
|
||||
</if>
|
||||
<else-if type="bill legislation" match="any">
|
||||
<group delimiter=", " prefix=", ">
|
||||
<choose>
|
||||
<if variable="number">
|
||||
<!--There's a public law number-->
|
||||
<text variable="number" prefix="Pub. L. No. "/>
|
||||
<group delimiter=" ">
|
||||
<!--change to label variable="section" as that becomes available -->
|
||||
<text term="section" form="symbol"/>
|
||||
<text variable="section"/>
|
||||
</group>
|
||||
<group delimiter=" ">
|
||||
<text variable="volume"/>
|
||||
<text variable="container-title"/>
|
||||
<text variable="page-first"/>
|
||||
</group>
|
||||
</if>
|
||||
<else>
|
||||
<group delimiter=" ">
|
||||
<text variable="volume"/>
|
||||
<text variable="container-title"/>
|
||||
<!--change to label variable="section" as that becomes available -->
|
||||
<text term="section" form="symbol"/>
|
||||
<text variable="section"/>
|
||||
</group>
|
||||
</else>
|
||||
</choose>
|
||||
</group>
|
||||
</else-if>
|
||||
</choose>
|
||||
</macro>
|
||||
<macro name="original-date">
|
||||
<choose>
|
||||
<if variable="original-date">
|
||||
<group prefix="(" suffix=")" delimiter=" ">
|
||||
<!---This should be localized-->
|
||||
<text value="Original work published"/>
|
||||
<date variable="original-date" form="text"/>
|
||||
</group>
|
||||
</if>
|
||||
</choose>
|
||||
</macro>
|
||||
<citation et-al-min="3" et-al-use-first="1" et-al-subsequent-min="3" et-al-subsequent-use-first="1" disambiguate-add-year-suffix="true" disambiguate-add-names="true" disambiguate-add-givenname="true" collapse="year" givenname-disambiguation-rule="primary-name">
|
||||
<sort>
|
||||
<key macro="author"/>
|
||||
<key macro="issued-sort"/>
|
||||
</sort>
|
||||
<layout prefix="(" suffix=")" delimiter="; ">
|
||||
<group delimiter=", ">
|
||||
<text macro="author-short"/>
|
||||
<text macro="issued-year"/>
|
||||
<text macro="citation-locator"/>
|
||||
</group>
|
||||
</layout>
|
||||
</citation>
|
||||
<bibliography hanging-indent="true" et-al-min="8" et-al-use-first="6" et-al-use-last="true" entry-spacing="0" line-spacing="2">
|
||||
<sort>
|
||||
<key macro="author"/>
|
||||
<key macro="issued-sort" sort="ascending"/>
|
||||
<key macro="title"/>
|
||||
</sort>
|
||||
<layout>
|
||||
<group suffix=".">
|
||||
<group delimiter=". ">
|
||||
<text macro="author"/>
|
||||
<text macro="issued"/>
|
||||
<text macro="title-plus-extra"/>
|
||||
<text macro="container"/>
|
||||
</group>
|
||||
<text macro="legal-cites"/>
|
||||
<text macro="locators"/>
|
||||
<group delimiter=", " prefix=". ">
|
||||
<text macro="event"/>
|
||||
<text macro="publisher"/>
|
||||
</group>
|
||||
</group>
|
||||
<text macro="access" prefix=" "/>
|
||||
<text macro="original-date" prefix=" "/>
|
||||
</layout>
|
||||
</bibliography>
|
||||
</style>
|
||||
25
assets/revealjs/clone_title_slide.html
Normal file
@@ -0,0 +1,25 @@
|
||||
<!--
|
||||
Below is the original version of: https://stackoverflow.com/questions/76261113/repeat-title-slide-at-end-of-reveal-js-presentation-and-add-additionnal-slides-a
|
||||
Which *clones* the title slide to the placeholder slide.
|
||||
You can add the placeholder slide like this:
|
||||
## {.placeholder-for-titleSlide visibility="uncounted"}
|
||||
-->
|
||||
|
||||
<script>
|
||||
function move_titleSlide() {
|
||||
var titleSlide = document.querySelector('section#title-slide');
|
||||
var titleSlideClone = titleSlide.cloneNode(true);
|
||||
titleSlideClone.id = 'title-slide-cloned';
|
||||
var placeholder = document.querySelector('section.placeholder-for-titleSlide');
|
||||
var visibility = placeholder.getAttribute('data-visibility');
|
||||
if (visibility !== null) {
|
||||
titleSlideClone.setAttribute('data-visibility', visibility);
|
||||
}
|
||||
placeholder.replaceWith(titleSlideClone);
|
||||
Reveal.sync();
|
||||
}
|
||||
|
||||
window.document.addEventListener("DOMContentLoaded", function (event) {
|
||||
move_titleSlide();
|
||||
});
|
||||
</script>
|
||||
35
assets/revealjs/custom.html
Normal file
@@ -0,0 +1,35 @@
|
||||
<script src="assets/revealjs/custom.js"></script>
|
||||
|
||||
<div
|
||||
style="position: fixed; bottom: 10px; right: 20px; display: flex; justify-content: flex-end; align-items: center; gap: 20px; flex-wrap: wrap;">
|
||||
<a href="https://www.uni-due.de/">
|
||||
<img src="assets/ude_signet.svg" alt="Uni Duisburg-Essen Logo" style="height: 4vh; width: auto;">
|
||||
</a>
|
||||
<a href="https://www.hemf.wiwi.uni-due.de/en/">
|
||||
<img src="assets/hecf_signet.svg" alt="HECF Logo" style="height: 4vh; width: auto;">
|
||||
</a>
|
||||
</div>
|
||||
|
||||
<script>
|
||||
function move_titleSlide() {
|
||||
var titleSlide = document.querySelector('section#title-slide');
|
||||
var placeholder = document.querySelector('section.placeholder-for-titleSlide');
|
||||
|
||||
if (titleSlide && placeholder) {
|
||||
// Transfer visibility attribute from placeholder to title slide
|
||||
var visibility = placeholder.getAttribute('data-visibility');
|
||||
if (visibility !== null) {
|
||||
titleSlide.setAttribute('data-visibility', visibility);
|
||||
}
|
||||
|
||||
// Move the title slide to replace the placeholder
|
||||
placeholder.parentNode.replaceChild(titleSlide, placeholder);
|
||||
|
||||
Reveal.sync();
|
||||
}
|
||||
}
|
||||
|
||||
window.document.addEventListener("DOMContentLoaded", function (event) {
|
||||
move_titleSlide();
|
||||
});
|
||||
</script>
|
||||
7
assets/revealjs/custom.js
Normal file
@@ -0,0 +1,7 @@
|
||||
window.MathJax = {
|
||||
tex: {
|
||||
tags: 'ams'
|
||||
},
|
||||
displayAlign: "left",
|
||||
displayIndent: "0em",
|
||||
};
|
||||
254
assets/revealjs/custom.scss
Normal file
@@ -0,0 +1,254 @@
|
||||
:root {
|
||||
--col_lightgray: #e7e7e7;
|
||||
--col_blue: #000088;
|
||||
--col_smooth_expost: #a7008b;
|
||||
--col_constant: #dd9002;
|
||||
--col_optimum: #666666;
|
||||
--col_smooth: #187a00;
|
||||
--col_pointwise: #008790;
|
||||
--col_green: #61B94C;
|
||||
--col_orange: #ffa600;
|
||||
--col_yellow: #FCE135;
|
||||
--col_amber_1: #FFF8E0FF;
|
||||
--col_amber_2: #FFEBB2FF;
|
||||
--col_amber_3: #FFDF81FF;
|
||||
--col_amber_4: #FFD44EFF;
|
||||
--col_amber_5: #FFCA27FF;
|
||||
--col_amber_6: #FFC006FF;
|
||||
--col_amber_7: #FFB200FF;
|
||||
--col_amber_8: #FF9F00FF;
|
||||
--col_amber_9: #FF8E00FF;
|
||||
--col_amber_10: #FF6E00FF;
|
||||
--col_blue_1: #E3F2FDFF;
|
||||
--col_blue_2: #BADEFAFF;
|
||||
--col_blue_3: #90CAF8FF;
|
||||
--col_blue_4: #64B4F6FF;
|
||||
--col_blue_5: #41A5F4FF;
|
||||
--col_blue_6: #2096F2FF;
|
||||
--col_blue_7: #1E87E5FF;
|
||||
--col_blue_8: #1976D2FF;
|
||||
--col_blue_9: #1465BFFF;
|
||||
--col_blue_10: #0C46A0FF;
|
||||
--col_blue-grey_1: #EBEEF1FF;
|
||||
--col_blue-grey_2: #CED8DCFF;
|
||||
--col_blue-grey_3: #B0BEC5FF;
|
||||
--col_blue-grey_4: #90A4ADFF;
|
||||
--col_blue-grey_5: #78909BFF;
|
||||
--col_blue-grey_6: #5F7D8BFF;
|
||||
--col_blue-grey_7: #536D79FF;
|
||||
--col_blue-grey_8: #455964FF;
|
||||
--col_blue-grey_9: #37464EFF;
|
||||
--col_blue-grey_10: #263238FF;
|
||||
--col_brown_1: #EEEBE9FF;
|
||||
--col_brown_2: #D7CCC7FF;
|
||||
--col_brown_3: #BBAAA4FF;
|
||||
--col_brown_4: #A0877FFF;
|
||||
--col_brown_5: #8C6D63FF;
|
||||
--col_brown_6: #795447FF;
|
||||
--col_brown_7: #6C4C40FF;
|
||||
--col_brown_8: #5D3F37FF;
|
||||
--col_brown_9: #4D332DFF;
|
||||
--col_brown_10: #3E2622FF;
|
||||
--col_cyan_1: #DFF7F9FF;
|
||||
--col_cyan_2: #B2EBF2FF;
|
||||
--col_cyan_3: #7FDEEAFF;
|
||||
--col_cyan_4: #4CD0E0FF;
|
||||
--col_cyan_5: #26C5D9FF;
|
||||
--col_cyan_6: #00BBD3FF;
|
||||
--col_cyan_7: #00ACC0FF;
|
||||
--col_cyan_8: #0097A6FF;
|
||||
--col_cyan_9: #00838EFF;
|
||||
--col_cyan_10: #005F64FF;
|
||||
--col_deep-orange_1: #FAE9E6FF;
|
||||
--col_deep-orange_2: #FFCCBBFF;
|
||||
--col_deep-orange_3: #FFAB91FF;
|
||||
--col_deep-orange_4: #FF8A65FF;
|
||||
--col_deep-orange_5: #FF7043FF;
|
||||
--col_deep-orange_6: #FF5721FF;
|
||||
--col_deep-orange_7: #F3511EFF;
|
||||
--col_deep-orange_8: #E54A19FF;
|
||||
--col_deep-orange_9: #D84314FF;
|
||||
--col_deep-orange_10: #BF350CFF;
|
||||
--col_deep-purple_1: #ECE6F6FF;
|
||||
--col_deep-purple_2: #D1C4E9FF;
|
||||
--col_deep-purple_3: #B29DDAFF;
|
||||
--col_deep-purple_4: #9474CCFF;
|
||||
--col_deep-purple_5: #7E57C1FF;
|
||||
--col_deep-purple_6: #6639B7FF;
|
||||
--col_deep-purple_7: #5E34B1FF;
|
||||
--col_deep-purple_8: #512CA7FF;
|
||||
--col_deep-purple_9: #45269FFF;
|
||||
--col_deep-purple_10: #311A92FF;
|
||||
--col_green_1: #E7F4E9FF;
|
||||
--col_green_2: #C7E5C9FF;
|
||||
--col_green_3: #A5D6A6FF;
|
||||
--col_green_4: #80C684FF;
|
||||
--col_green_5: #66BA6AFF;
|
||||
--col_green_6: #4CAE50FF;
|
||||
--col_green_7: #439F46FF;
|
||||
--col_green_8: #388D3BFF;
|
||||
--col_green_9: #2D7D32FF;
|
||||
--col_green_10: #1A5E1FFF;
|
||||
--col_grey_1: #F9F9F9FF;
|
||||
--col_grey_2: #F4F4F4FF;
|
||||
--col_grey_3: #EDEDEDFF;
|
||||
--col_grey_4: #DFDFDFFF;
|
||||
--col_grey_5: #BDBDBDFF;
|
||||
--col_grey_6: #9E9E9EFF;
|
||||
--col_grey_7: #747474FF;
|
||||
--col_grey_8: #606060FF;
|
||||
--col_grey_9: #414141FF;
|
||||
--col_grey_10: #202020FF;
|
||||
--col_indigo_1: #E7EAF6FF;
|
||||
--col_indigo_2: #C5CAE9FF;
|
||||
--col_indigo_3: #9FA7D9FF;
|
||||
--col_indigo_4: #7985CBFF;
|
||||
--col_indigo_5: #5B6BBFFF;
|
||||
--col_indigo_6: #3F51B4FF;
|
||||
--col_indigo_7: #3948ABFF;
|
||||
--col_indigo_8: #303F9FFF;
|
||||
--col_indigo_9: #273492FF;
|
||||
--col_indigo_10: #19227EFF;
|
||||
--col_light-blue_1: #E0F4FEFF;
|
||||
--col_light-blue_2: #B2E5FCFF;
|
||||
--col_light-blue_3: #80D3F9FF;
|
||||
--col_light-blue_4: #4EC3F7FF;
|
||||
--col_light-blue_5: #28B6F6FF;
|
||||
--col_light-blue_6: #02A9F3FF;
|
||||
--col_light-blue_7: #029AE5FF;
|
||||
--col_light-blue_8: #0187D1FF;
|
||||
--col_light-blue_9: #0177BDFF;
|
||||
--col_light-blue_10: #00579AFF;
|
||||
--col_light-green_1: #F1F8E9FF;
|
||||
--col_light-green_2: #DCECC7FF;
|
||||
--col_light-green_3: #C5E0A5FF;
|
||||
--col_light-green_4: #ADD480FF;
|
||||
--col_light-green_5: #9BCC65FF;
|
||||
--col_light-green_6: #8BC34AFF;
|
||||
--col_light-green_7: #7BB241FF;
|
||||
--col_light-green_8: #679F38FF;
|
||||
--col_light-green_9: #548B2EFF;
|
||||
--col_light-green_10: #33681EFF;
|
||||
--col_lime_1: #F8FAE6FF;
|
||||
--col_lime_2: #F0F3C3FF;
|
||||
--col_lime_3: #E5ED9BFF;
|
||||
--col_lime_4: #DCE674FF;
|
||||
--col_lime_5: #D3E057FF;
|
||||
--col_lime_6: #CCDC39FF;
|
||||
--col_lime_7: #BFCA33FF;
|
||||
--col_lime_8: #AEB32BFF;
|
||||
--col_lime_9: #9E9D24FF;
|
||||
--col_lime_10: #817717FF;
|
||||
--col_orange_1: #FFF2DFFF;
|
||||
--col_orange_2: #FFDFB2FF;
|
||||
--col_orange_3: #FFCC7FFF;
|
||||
--col_orange_4: #FFB74CFF;
|
||||
--col_orange_5: #FFA626FF;
|
||||
--col_orange_6: #FF9800FF;
|
||||
--col_orange_7: #FA8C00FF;
|
||||
--col_orange_8: #F47B00FF;
|
||||
--col_orange_9: #EE6C00FF;
|
||||
--col_orange_10: #E55100FF;
|
||||
--col_pink_1: #FCE4EBFF;
|
||||
--col_pink_2: #F8BAD0FF;
|
||||
--col_pink_3: #F38EB1FF;
|
||||
--col_pink_4: #F06192FF;
|
||||
--col_pink_5: #EB3F79FF;
|
||||
--col_pink_6: #E91E63FF;
|
||||
--col_pink_7: #D81A5FFF;
|
||||
--col_pink_8: #C1185AFF;
|
||||
--col_pink_9: #AC1357FF;
|
||||
--col_pink_10: #870D4EFF;
|
||||
--col_purple_1: #F2E5F4FF;
|
||||
--col_purple_2: #E0BEE6FF;
|
||||
--col_purple_3: #CD92D8FF;
|
||||
--col_purple_4: #B967C7FF;
|
||||
--col_purple_5: #AB46BBFF;
|
||||
--col_purple_6: #9B26B0FF;
|
||||
--col_purple_7: #8D24AAFF;
|
||||
--col_purple_8: #7A1FA1FF;
|
||||
--col_purple_9: #6A1A99FF;
|
||||
--col_purple_10: #4A138CFF;
|
||||
--col_red_1: #FFEBEDFF;
|
||||
--col_red_2: #FFCCD2FF;
|
||||
--col_red_3: #EE9999FF;
|
||||
--col_red_4: #E57272FF;
|
||||
--col_red_5: #EE5250FF;
|
||||
--col_red_6: #F34335FF;
|
||||
--col_red_7: #E53934FF;
|
||||
--col_red_8: #D22E2EFF;
|
||||
--col_red_9: #C52727FF;
|
||||
--col_red_10: #B71B1BFF;
|
||||
--col_teal_1: #DFF2F1FF;
|
||||
--col_teal_2: #B2DFDAFF;
|
||||
--col_teal_3: #7FCBC4FF;
|
||||
--col_teal_4: #4CB6ACFF;
|
||||
--col_teal_5: #26A599FF;
|
||||
--col_teal_6: #009687FF;
|
||||
--col_teal_7: #00887AFF;
|
||||
--col_teal_8: #00796BFF;
|
||||
--col_teal_9: #00685BFF;
|
||||
--col_teal_10: #004C3FFF;
|
||||
--col_yellow_1: #FFFDE6FF;
|
||||
--col_yellow_2: #FFF8C4FF;
|
||||
--col_yellow_3: #FFF49DFF;
|
||||
--col_yellow_4: #FFF176FF;
|
||||
--col_yellow_5: #FFED58FF;
|
||||
--col_yellow_6: #FFEB3AFF;
|
||||
--col_yellow_7: #FDD834FF;
|
||||
--col_yellow_8: #FABF2CFF;
|
||||
--col_yellow_9: #F8A725FF;
|
||||
--col_yellow_10: #F47F17FF;
|
||||
}
|
||||
|
||||
/*-- scss:defaults --*/
|
||||
|
||||
// $body-bg: #ffffff;
|
||||
// $body-color: #7a6f69;
|
||||
// $link-color: #005088;
|
||||
// $selection-color: #00b0dc;
|
||||
|
||||
// $presentation-heading-color: $selection-color;
|
||||
// $tabset-border-color: #bbb3b0;
|
||||
|
||||
/*-- scss:rules --*/
|
||||
.slide-number,
|
||||
.reveal.has-logo .slide-number {
|
||||
bottom: 14px !important;
|
||||
left: 50px !important;
|
||||
top: unset !important;
|
||||
color: #777777 !important;
|
||||
}
|
||||
|
||||
// Alternatively center the slide numbers
|
||||
// .slide-number,
|
||||
// .reveal.has-logo .slide-number {
|
||||
// bottom: 10px !important;
|
||||
// left: 50% !important;
|
||||
// top: unset !important;
|
||||
// color: #777777 !important;
|
||||
// }
|
||||
|
||||
.sup-zero-width {
|
||||
display: inline-block;
|
||||
vertical-align: super;
|
||||
font-size: smaller;
|
||||
width: 0px;
|
||||
}
|
||||
|
||||
.zero-width {
|
||||
display: inline-block;
|
||||
width: 0px;
|
||||
}
|
||||
|
||||
.fa {
|
||||
width: 1.25em;
|
||||
text-align: center;
|
||||
}
|
||||
|
||||
/* Grey out links inside a row with class "greyed-out" */
|
||||
tr.greyed-out,
|
||||
tr.greyed-out a {
|
||||
color: var(--col_grey_3) !important;
|
||||
text-decoration: none !important;
|
||||
}
|
||||
36
assets/revealjs/move_title_slide.html
Normal file
@@ -0,0 +1,36 @@
|
||||
<!--
|
||||
Below is an adjusted version of: https://stackoverflow.com/questions/76261113/repeat-title-slide-at-end-of-reveal-js-presentation-and-add-additionnal-slides-a
|
||||
Which *moves* the title slide to the placeholder slide.
|
||||
You can add the placeholder slide like this:
|
||||
## {.placeholder-for-titleSlide visibility="uncounted"}
|
||||
-->
|
||||
|
||||
<script>
|
||||
function move_titleSlide() {
|
||||
var titleSlide = document.querySelector('section#title-slide');
|
||||
var placeholder = document.querySelector('section.placeholder-for-titleSlide');
|
||||
|
||||
if (titleSlide && placeholder) {
|
||||
// Transfer visibility attribute from placeholder to title slide
|
||||
var visibility = placeholder.getAttribute('data-visibility');
|
||||
if (visibility !== null) {
|
||||
titleSlide.setAttribute('data-visibility', visibility);
|
||||
}
|
||||
|
||||
// Move the title slide to replace the placeholder
|
||||
placeholder.parentNode.replaceChild(titleSlide, placeholder);
|
||||
|
||||
Reveal.sync();
|
||||
}
|
||||
}
|
||||
|
||||
window.document.addEventListener("DOMContentLoaded", function (event) {
|
||||
move_titleSlide();
|
||||
});
|
||||
</script>
|
||||
|
||||
<style>
|
||||
#title-slide .subtitle {
|
||||
margin-bottom: 2.5rem
|
||||
}
|
||||
</style>
|
||||
172
assets/revealjs/sydney.scss
Normal file
@@ -0,0 +1,172 @@
|
||||
// See https://quarto.org/docs/presentations/revealjs/themes.html#saas-variables
|
||||
|
||||
$brand-red: #004c93;
|
||||
$brand-blue: #efe4bf;
|
||||
$brand-yellow: #ec7206;
|
||||
$brand-charcoal: #424242;
|
||||
$brand-gray: #F1F1F1;
|
||||
$brand-grey: #F1F1F1;
|
||||
|
||||
/*-- scss:defaults --*/
|
||||
|
||||
// icons
|
||||
@import url("https://cdn.jsdelivr.net/npm/bootstrap-icons@1.8.1/font/bootstrap-icons.css");
|
||||
|
||||
// fonts
|
||||
@import url('https://fonts.googleapis.com/css2?family=Roboto');
|
||||
@import url(https://fonts.googleapis.com/css?family=Roboto+Condensed);
|
||||
@import url(https://fonts.googleapis.com/css?family=Source+Code+Pro);
|
||||
@import url('https://fonts.googleapis.com/css2?family=Patrick+Hand&display=swap');
|
||||
|
||||
$roboto: 'Roboto', Arial, sans-serif;
|
||||
$roboto-cond: 'Roboto Condensed', Arial, sans-serif;
|
||||
$code-font: 'Source Code Pro', 'Lucida Console', Monaco, monospace;
|
||||
$blockquote-font: 'Patrick Hand', cursive;
|
||||
|
||||
// colors
|
||||
$body-bg: #fff;
|
||||
$body-color: #222;
|
||||
$link-color: #2a76dd;
|
||||
$selection-bg: lighten($link-color, 25%);
|
||||
|
||||
|
||||
// website
|
||||
$font-family-sans-serif: $roboto !default;
|
||||
$font-family-monospace: $code-font !default;
|
||||
$body-color: $brand-charcoal;
|
||||
$navbar-bg: #333333;
|
||||
//$navbar-color: #0F2E3D;
|
||||
$link-color: $brand-red;
|
||||
|
||||
// headings
|
||||
$presentation-heading-font: $roboto-cond !default;
|
||||
$presentation-heading-color: #383d3d !default;
|
||||
|
||||
// title slide
|
||||
$presentation-title-slide-text-align: left;
|
||||
|
||||
// body
|
||||
$presentation-font-size-root: 28px; // default is 40px
|
||||
$presentation-font-smaller: 0.9 !default;
|
||||
$presentation-line-height: 1.3; // default is 1.3
|
||||
|
||||
// code blocks
|
||||
|
||||
$code-block-bg: $brand-grey;
|
||||
// $code-block-border-color: lighten($body-color, 60%);
|
||||
$code-block-font-size: 0.75em;
|
||||
// $code-color: $brand-charcoal; // var(–quarto-hl-fu-color);
|
||||
// $code-bg: transparent;
|
||||
|
||||
|
||||
/*-- scss:rules --*/
|
||||
|
||||
|
||||
// .reveal .slide-background:first-child {
|
||||
// background-image: url("https://raw.githubusercontent.com/DATA2002/data/master/usydlogo-white.svg");
|
||||
// background-repeat: no-repeat;
|
||||
// background-position: 95% 95%;
|
||||
// background-size: 15%;
|
||||
// background-color: $brand-red;
|
||||
// }
|
||||
|
||||
|
||||
.reveal .slide aside,
|
||||
.reveal .slide div.aside {
|
||||
position: absolute;
|
||||
bottom: 20px;
|
||||
font-size: 0.6em;
|
||||
color: #8f8f8f;
|
||||
}
|
||||
|
||||
.red {
|
||||
color: $brand-red;
|
||||
}
|
||||
|
||||
.blue {
|
||||
color: $brand-blue;
|
||||
}
|
||||
|
||||
.slide smaller {
|
||||
font-size: $presentation-font-smaller;
|
||||
}
|
||||
|
||||
.blockquote,
|
||||
.reveal .slide blockquote {
|
||||
/* border-left: 3px solid $text-muted; */
|
||||
/* padding-left: 0.5em; */
|
||||
|
||||
display: block;
|
||||
position: relative;
|
||||
font-family: $blockquote-font;
|
||||
font-size: 1.2em;
|
||||
/* font-style: italic; */
|
||||
color: $brand-charcoal;
|
||||
margin-top: 0.1em;
|
||||
margin-bottom: 0.2em;
|
||||
border-left: solid 0.3rem $brand-blue;
|
||||
/* matches with .callouts */
|
||||
border-top: solid 1px silver;
|
||||
border-bottom: solid 1px silver;
|
||||
border-right: solid 1px silver;
|
||||
/* box-shadow: 0 0 6px rgba(0,0,0,0.5); */
|
||||
/* background-color: #e64626; */
|
||||
|
||||
/* padding: 0.5em; */
|
||||
-moz-border-radius: 5px;
|
||||
-webkit-border-radius: 5px;
|
||||
|
||||
|
||||
width: unset;
|
||||
margin: var(--r-block-margin) auto;
|
||||
padding: 0.625rem 1.75rem;
|
||||
}
|
||||
|
||||
.reveal .slides section .callout {
|
||||
font-size: inherit;
|
||||
}
|
||||
|
||||
.reveal .callout.callout-style-simple .callout-body,
|
||||
.reveal .callout.callout-style-default .callout-body,
|
||||
.reveal .callout.callout-style-simple div.callout-caption,
|
||||
.reveal .callout.callout-style-default div.callout-caption {
|
||||
font-size: inherit;
|
||||
}
|
||||
|
||||
.reveal .callout.callout-style-default .callout-icon::before,
|
||||
.reveal .callout.callout-style-simple .callout-icon::before {
|
||||
height: 2rem;
|
||||
width: 2rem;
|
||||
background-size: 2rem 2rem;
|
||||
}
|
||||
|
||||
.reveal .title-slide {
|
||||
background-color: $brand-blue;
|
||||
}
|
||||
|
||||
// customisations for printing to pdf
|
||||
|
||||
.print-pdf .reveal .title-slide {
|
||||
background-color: #FFFFFF;
|
||||
}
|
||||
|
||||
.print-pdf {
|
||||
|
||||
section.has-dark-background,
|
||||
section.has-dark-background h1,
|
||||
section.has-dark-background h2,
|
||||
section.has-dark-background h3,
|
||||
section.has-dark-background h4,
|
||||
section.has-dark-background h5,
|
||||
section.has-dark-background h6 {
|
||||
color: #000000 !important;
|
||||
}
|
||||
}
|
||||
|
||||
.print-pdf .reveal .slide-background {
|
||||
background-color: #FFFFFF !important;
|
||||
}
|
||||
|
||||
.print-pdf .reveal .has-dark-background {
|
||||
color: #222 !important;
|
||||
}
|
||||
66
assets/ude_logo.svg
Normal file
@@ -0,0 +1,66 @@
|
||||
<?xml version="1.0" encoding="utf-8"?>
|
||||
<svg version="1.2" viewBox="0 0 1052.3625 414.5675" height="414.5675" width="1052.3625" id="ude-logo" preserveAspectRatio="none" xmlns="http://www.w3.org/2000/svg">
|
||||
<style type="text/css">
|
||||
path { fill:#003B7A;fill-opacity:1;fill-rule:nonzero;stroke:none }
|
||||
</style>
|
||||
<defs id="defs6">
|
||||
<clipPath id="clipPath16" clipPathUnits="userSpaceOnUse">
|
||||
<path id="path18" d="m 0,331.654 841.89,0 L 841.89,0 0,0 0,331.654 Z"/>
|
||||
</clipPath>
|
||||
</defs>
|
||||
<g transform="matrix(1.25,0,0,-1.25,0,414.5675)">
|
||||
<g>
|
||||
<g clip-path="url(#clipPath16)">
|
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<g transform="translate(59.0718,56.833)">
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<path d="m 0,0 c 0,5.246 -1.094,7.721 -4.588,7.721 -8.666,0 -13.325,-17.549 -13.325,-29.418 0,-5.17 1.093,-7.645 4.659,-7.645 C -4.588,-29.342 0,-11.869 0,0 m -14.271,-36.988 c -8.595,0 -13.474,5.24 -13.474,15.074 0,17.035 7.501,37.279 24.249,37.279 8.446,0 13.324,-5.314 13.324,-15.146 0,-16.963 -7.426,-37.207 -24.099,-37.207"/>
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</g>
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<g transform="translate(82.8135,20.5752)">
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<path d="m 0,0 c -1.384,-6.846 -4.079,-14.199 -13.98,-14.199 -3.352,0 -6.482,0.437 -6.482,1.238 0,0.287 0.072,0.506 0.145,0.799 l 1.529,5.099 c 0.147,0.36 0.294,0.508 0.512,0.508 0.216,0 1.455,-0.365 2.984,-0.365 4.951,0 5.825,3.348 6.772,8.008 l 5.68,28.836 -5.172,0 c -0.436,0 -1.018,0.074 -1.018,0.73 0,0.291 0.075,0.58 0.144,0.871 l 0.874,4.082 c 0.075,0.651 0.219,0.87 1.021,0.87 l 5.388,0 0.875,4.589 c 1.092,5.897 2.985,11.651 12.959,11.651 3.058,0 7.355,-0.949 7.355,-2.041 0,-0.221 -0.074,-0.363 -0.146,-0.582 L 17.694,44.996 C 17.475,44.559 17.256,44.49 17.11,44.49 c -0.728,0 -2.184,0.944 -4.369,0.944 -3.786,0 -4.296,-2.838 -4.951,-5.825 l -0.654,-3.132 8.3,0 c 0.655,0 0.874,-0.364 0.874,-0.653 0,-0.293 -0.146,-0.586 -0.219,-0.875 L 14.78,30.727 c -0.219,-0.655 -0.291,-0.803 -1.019,-0.803 l -7.864,0 L 0,0 Z"/>
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</g>
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<g transform="translate(108.4463,20.5752)">
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<path d="m 0,0 c -1.384,-6.846 -4.079,-14.199 -13.98,-14.199 -3.35,0 -6.482,0.437 -6.482,1.238 0,0.287 0.072,0.506 0.147,0.799 l 1.528,5.099 c 0.146,0.36 0.29,0.508 0.509,0.508 0.218,0 1.456,-0.365 2.986,-0.365 4.954,0 5.825,3.348 6.772,8.008 l 5.679,28.836 -5.169,0 c -0.437,0 -1.021,0.074 -1.021,0.73 0,0.291 0.073,0.58 0.148,0.871 l 0.873,4.082 c 0.071,0.651 0.219,0.87 1.019,0.87 l 5.388,0 0.873,4.589 c 1.092,5.897 2.986,11.651 12.962,11.651 3.059,0 7.354,-0.949 7.354,-2.041 0,-0.221 -0.072,-0.363 -0.146,-0.582 L 17.691,44.996 C 17.475,44.559 17.257,44.49 17.11,44.49 c -0.728,0 -2.184,0.944 -4.367,0.944 -3.788,0 -4.298,-2.838 -4.953,-5.825 l -0.656,-3.132 8.301,0 c 0.656,0 0.875,-0.364 0.875,-0.653 0,-0.293 -0.146,-0.586 -0.219,-0.875 L 14.78,30.727 c -0.218,-0.655 -0.291,-0.803 -1.019,-0.803 l -7.865,0 L 0,0 Z"/>
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</g>
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<g transform="translate(132.6211,41.4697)">
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<path d="m 0,0 c 3.132,0 12.889,0 12.889,6.697 0,1.893 -1.165,3.573 -3.351,3.573 C 2.694,10.27 0.655,2.693 0,0 m 16.893,-16.453 c 0.073,-0.219 0.219,-0.438 0.219,-0.656 0,-0.95 -6.772,-4.516 -14.199,-4.516 -8.736,0 -12.67,5.459 -12.67,13.543 0,14.562 9.394,24.906 20.607,24.906 6.846,0 10.776,-3.793 10.776,-9.615 0,-13.76 -18.494,-13.76 -22.645,-13.76 0,-2.185 -0.582,-7.791 6.262,-7.791 4.295,0 8.155,2.91 9.248,2.91 0.363,0 0.438,-0.216 0.582,-0.509 l 1.82,-4.512 z"/>
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</g>
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<g transform="translate(183.5234,21.9561)" id="g36">
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<path d="m 0,0 c -0.145,-0.801 -0.291,-0.873 -1.019,-0.873 l -6.771,0 c -0.582,0 -0.947,0.148 -0.947,0.728 0,0.219 0.072,0.508 0.072,0.801 l 4.805,20.752 c 0.365,1.455 0.656,2.91 0.656,4.442 0,1.673 -0.656,2.841 -2.185,2.841 -6.698,0 -9.101,-9.031 -10.266,-14.273 L -18.785,0 c -0.146,-0.801 -0.293,-0.873 -1.021,-0.873 l -6.771,0 c -0.584,0 -0.946,0.148 -0.946,0.728 0,0.219 0.074,0.508 0.074,0.801 l 4.948,21.918 c 0.438,1.819 0.875,3.637 0.875,5.969 0,2.186 -0.656,3.203 -0.656,4.516 0,0.509 0.511,0.656 0.874,0.798 l 5.827,2.26 c 0.219,0.071 0.363,0.221 0.727,0.221 0.802,0 1.457,-3.279 1.457,-7.359 1.965,2.33 6.116,7.359 12.085,7.359 4.734,0 7.355,-3.643 7.355,-7.647 0,-1.892 -0.29,-3.859 -0.727,-5.683 L 0,0 Z"/>
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</g>
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<g transform="translate(230.2773,65.1338)" id="g40">
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<path id="path42" d="m 0,0 c -2.257,0 -4.079,1.822 -4.079,4.078 0,2.186 1.822,4.08 4.079,4.08 2.184,0 4.077,-1.894 4.077,-4.08 C 4.077,1.822 2.184,0 0,0 m -6.917,-42.594 c -0.148,-0.658 -0.22,-1.457 -0.947,-1.457 l -3.861,0 c -0.437,0 -0.728,0.149 -0.728,0.367 0,0.288 0.073,0.649 0.147,0.87 l 6.262,29.49 -5.752,0 c -0.51,0 -0.584,0.219 -0.584,0.511 0,0.145 0,0.288 0.074,0.583 l 0.51,2.328 c 0.146,0.511 0.365,0.8 0.874,0.8 l 9.685,0 c 1.017,0 1.162,-0.07 1.162,-0.582 0,-0.435 -0.218,-1.017 -0.362,-1.818 l -6.48,-31.092 z"/>
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</g>
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<g transform="translate(275.9316,46.1318)">
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<path id="path46" d="m 0,0 c 0.219,0.949 0.438,1.967 0.438,2.912 0,2.041 -1.092,3.129 -3.277,3.129 -7.646,0 -9.902,-7.643 -11.65,-15.506 l -3.277,-14.855 c -0.147,-0.512 -0.29,-0.729 -0.875,-0.729 l -3.786,0 c -0.364,0 -0.582,0.149 -0.582,0.436 0,0.144 0,0.363 0.074,0.511 L -17.838,0 c 0.218,0.949 0.437,1.967 0.437,2.912 0,2.041 -1.093,3.129 -3.279,3.129 -7.645,0 -10.483,-9.684 -11.503,-14.488 l -3.352,-15.873 c -0.144,-0.512 -0.287,-0.729 -0.871,-0.729 l -3.788,0 c -0.363,0 -0.582,0.149 -0.582,0.436 0,0.144 0,0.363 0.075,0.511 l 5.166,24.463 c 0.294,1.532 0.513,3.131 0.513,4.155 0,1.453 -0.293,2.91 -0.582,4.367 0,0.291 0.363,0.51 0.654,0.582 l 2.476,1.092 c 0.437,0.144 0.728,0.363 1.018,0.363 0.8,0 1.312,-1.82 1.312,-3.637 0,-1.461 -0.147,-2.33 -0.147,-3.279 l 0.147,0 c 2.402,3.496 5.898,6.916 11.65,6.916 3.495,0 6.116,-1.963 6.116,-6.916 l 0.145,0 C -9.685,7.5 -6.188,10.92 -0.654,10.92 3.132,10.92 5.972,8.957 5.972,5.098 5.972,3.348 5.607,1.674 5.244,0 L 0.072,-24.32 c -0.143,-0.512 -0.29,-0.729 -0.871,-0.729 l -3.788,0 c -0.364,0 -0.581,0.149 -0.581,0.436 0,0.144 0,0.363 0.073,0.511 L 0,0 Z"/>
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</g>
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<g transform="translate(320.9395,25.9619)" id="g48">
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<path id="path50" d="m 0,0 c 4.441,0 8.301,1.891 10.776,5.02 4.732,5.466 7.572,19.009 7.572,26 0,8.519 -4.661,9.099 -9.611,9.099 l -4.66,0 L -4.369,0 0,0 Z m 7.427,45 c 8.372,0 16.892,-0.293 16.892,-14.055 0,-7.134 -2.186,-17.256 -6.481,-25.486 C 13.687,-2.402 6.844,-4.879 -1.821,-4.879 l -8.667,0 c -0.362,0 -0.581,0.149 -0.581,0.512 L -0.729,44.27 C -0.583,44.852 -0.293,45 0.145,45 l 7.282,0 z"/>
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</g>
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<g transform="translate(371.4771,47.5127)" id="g52">
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</g>
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<ellipse style="fill: rgb(0, 76, 147);" cx="426.691" cy="309.51" rx="5.704" ry="5.711"/>
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<path d="M 515.046 363.294 C 515.046 364.269 514.514 364.803 513.539 364.803 L 505.201 364.803 C 504.226 364.803 503.782 364.269 503.782 363.294 L 503.782 329.191 L 503.782 322.619 C 503.782 321.642 504.314 321.109 505.378 321.109 L 513.539 320.932 C 514.514 320.932 515.046 321.464 515.046 322.442 L 515.046 363.294 Z" style="fill: rgb(0, 76, 147); text-wrap-mode: nowrap;"/>
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<ellipse style="fill: rgb(0, 76, 147);" cx="509.338" cy="309.501" rx="5.704" ry="5.711"/>
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</svg>
|
||||
|
After Width: | Height: | Size: 6.1 KiB |
@@ -79,7 +79,9 @@
|
||||
rPackages.gganimate
|
||||
rPackages.cowplot
|
||||
rPackages.xtable
|
||||
rPackages.ggsci
|
||||
rPackages.profoc
|
||||
rPackages.ggforce
|
||||
|
||||
];
|
||||
|
||||
|
||||
30005
index.html
Normal file
53
remove_unused_bibentries.sh
Executable file
@@ -0,0 +1,53 @@
|
||||
#!/bin/sh
|
||||
|
||||
# Path to your .bib file
|
||||
BIBFILE="assets/library.bib"
|
||||
|
||||
# Step 1: Extract all citation keys from the .bib file
|
||||
# This assumes keys follow immediately after @...{KEY,
|
||||
bibkeys=$(grep -oP '^@\w+\{\K[^,]+' "$BIBFILE")
|
||||
|
||||
# Step 2: Initialize array for unused keys
|
||||
unused=()
|
||||
|
||||
for key in $bibkeys; do
|
||||
if ! grep -qr "$key" . --include="*.qmd"; then
|
||||
unused+=("$key")
|
||||
fi
|
||||
done
|
||||
|
||||
if [ ${#unused[@]} -eq 0 ]; then
|
||||
echo "All citation keys are used."
|
||||
else
|
||||
echo "Unused citation keys:"
|
||||
for key in "${unused[@]}"; do
|
||||
echo " $key"
|
||||
done
|
||||
fi
|
||||
|
||||
# Step 5: Optional removal
|
||||
if [ ${#unused[@]} -gt 0 ]; then
|
||||
echo "Removing unused entries from $BIBFILE..."
|
||||
|
||||
awk -v keys="${unused[*]}" '
|
||||
BEGIN {
|
||||
split(keys, klist);
|
||||
for (i in klist) unused[klist[i]] = 1;
|
||||
skip = 0;
|
||||
}
|
||||
/^[[:space:]]*@/ {
|
||||
match($0, /^@\w+\{([^,]+),/, m);
|
||||
if (m[1] && unused[m[1]]) {
|
||||
skip = 1;
|
||||
next;
|
||||
}
|
||||
}
|
||||
skip && /^\s*}/ {
|
||||
skip = 0;
|
||||
next;
|
||||
}
|
||||
!skip
|
||||
' "$BIBFILE" > "$BIBFILE.tmp" && mv "$BIBFILE.tmp" "$BIBFILE"
|
||||
|
||||
echo "Done."
|
||||
fi
|
||||