Knot placement details, cross referencing etc.
This commit is contained in:
78
index.qmd
78
index.qmd
@@ -36,7 +36,7 @@ revealjs-plugins:
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- pointer
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---
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## Outline
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## Outline {.center}
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<!--
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Render with: quarto preview /home/jonathan/git/PHD-Presentation/25_07_phd_defense/index.qmd --no-browser --port 6074
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@@ -48,20 +48,17 @@ $$
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$$
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:::
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<br/>
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:::: {style="font-size: 150%;"}
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<i class="fa fa-fw fa-rocket" style="color:var(--col_grey_9);"></i>   [Research Motivation](#motivation)
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<i class="fa fa-fw fa-book" style="color:var(--col_grey_9);"></i>   Overview of the Thesis
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<i class="fa fa-fw fa-book" style="color:var(--col_grey_9);"></i>   [Overview of the Thesis](#sec-overview)
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<i class="fa fa-fw fa-code-merge" style="color:var(--col_grey_9);"></i>   Online Aggregation
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<i class="fa fa-fw fa-layer-group" style="color:var(--col_grey_9);"></i>   [Online Aggregation](#sec-crps-learning)
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<i class="fa fa-fw fa-fire-flame-simple" style="color:var(--col_grey_9);"></i>   Probabilistic Forecasting of European Carbon and Energy Prices
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<i class="fa fa-fw fa-newspaper" style="color:var(--col_grey_9);"></i>   Contributions & Outlook
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<i class="fa fa-fw fa-chart-line" style="color:var(--col_grey_9);"></i>   [Probabilistic Forecasting of European Carbon and Energy Prices](#sec-voldep)
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<i class="fa fa-fw fa-newspaper" style="color:var(--col_grey_9);"></i>   [Contributions & Outlook](#sec-conclusion)
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:::
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@@ -101,7 +98,7 @@ col_yellow <- "#FCE135"
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## Motivation
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## Overview of the Thesis {transition="fade" transition-speed="slow"}
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## Overview of the Thesis {transition="fade" transition-speed="slow" #sec-overview}
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<table style="width: 100%; border-collapse: separate; border-spacing: 0 1em; border: none;">
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<tr style="border: none;">
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@@ -162,7 +159,7 @@ col_yellow <- "#FCE135"
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</tr>
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</table>
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## Overview of the Thesis {transition="fade" transition-speed="slow"}
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## Overview of the Thesis {transition="fade" transition-speed="slow"}
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<table style="width: 100%; border-collapse: separate; border-spacing: 0 1em; border: none;">
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<tr style="border: none;">
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@@ -589,7 +586,7 @@ ggplot() +
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::::
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# CRPS Learning
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# CRPS Learning {#sec-crps-learning}
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Berrisch, J., & Ziel, F. [-@BERRISCH2023105221]. *Journal of Econometrics*, 237(2), 105221.
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@@ -2627,27 +2624,21 @@ chart = {
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::: {.column width="48%"}
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Basis specification `b_smooth_pr` is internally passed to `make_basis_mats()`:
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Non-central beta distribution @johnson1995continuous:
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```{r, echo = TRUE, eval = FALSE, cache = TRUE}
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mod <- online(
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y = Y,
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experts = experts,
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tau = 1:99 / 100,
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b_smooth_pr = list(
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knots = 9,
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mu = 0.3, # NEW
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sigma = 1,
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nonc = 0,
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tailweight = 1,
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deg = 3
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)
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)
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::: {style="font-size: 70%;"}
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\begin{equation*}
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\mathcal{B}(x, a, b, c) = \sum_{j=0}^{\infty} e^{-c/2} \frac{\left( \frac{c}{2} \right)^j}{j!} I_x \left( a + j , b \right)
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\end{equation*}
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::::
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```{r, fig.align="center", echo=FALSE, out.width = "1000px", cache = TRUE}
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knitr::include_graphics("assets/mcrps_learning/knot_placement.svg")
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```
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Knots are distributed using the generalized beta distribution.
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TODO: Add actual algorithm to backup slides
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<i class="fa fa-fw fa-triangle-exclamation" style="color:var(--col_orange_9);"></i> Penalty and $\lambda$ need to be adjusted accordingly @li2022general
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:::
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@@ -2657,6 +2648,27 @@ TODO: Add actual algorithm to backup slides
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::: {.column width="48%"}
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Using non equidistant knots in `profoc` is straightforward:
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```{r, echo = TRUE, eval = FALSE, cache = TRUE}
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mod <- online(
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y = Y,
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experts = experts,
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tau = 1:99 / 100,
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b_smooth_pr = list(
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knots = 9,
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mu = 0.3,
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sigma = 1,
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nonc = 0,
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tailweight = 1,
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deg = 3
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)
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)
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```
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Basis specification `b_smooth_pr` is internally passed to `make_basis_mats()`.
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<i class="fa fa-fw fa-check" style="color:var(--col_green_9);"></i> Profoc adjusts penatly and $\lambda$
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:::
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@@ -2716,7 +2728,7 @@ Pubications:
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::::
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# Modeling Volatility and Dependence of European Carbon and Energy Prices
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# Modeling Volatility and Dependence of European Carbon and Energy Prices {#sec-voldep}
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Berrisch, J., Pappert, S., Ziel, F., & Arsova, A. (2023). *Finance Research Letters*, 52, 103503.
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@@ -3482,6 +3494,10 @@ Accounting for heteroscedasticity or stabilizing the variance via log transforma
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::::
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## Conclusion
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## Contributions and Outlook {#sec-conclusion}
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## References
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