Add overview and motivation slides
This commit is contained in:
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index.qmd
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index.qmd
@@ -95,8 +95,81 @@ col_orange <- "#ffa600"
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col_yellow <- "#FCE135"
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col_yellow <- "#FCE135"
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```
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```
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## The beginning: June 2020
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<center>
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<img src="assets/allisonhorst/the_beginning_cropped.png">
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</center>
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## Motivation
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## Motivation
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:::: {.columns}
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::: {.column width="48%"}
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<table style="width: 100%; border-collapse: separate; border-spacing: 0 0.7em; border: none;">
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<tr style="border: none;">
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<td style="vertical-align: top; width: 1.5em; border: none;">
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<i class="fa fa-fw fa-network-wired" style="color:var(--col_green_10);"></i>
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</td>
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<td style="border: none;">
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Energy market liberalization created complex, interconnected trading systems
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</td>
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</tr>
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<tr style="border: none;">
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<td style="vertical-align: top; border: none;">
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<i class="fa fa-fw fa-wind" style="color:var(--col_green_10);"></i>
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</td>
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<td style="border: none;">
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Renewable energy transition introduces uncertainty and volatility from weather-dependent generation
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</td>
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</tr>
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<tr style="border: none;">
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<td style="vertical-align: top; border: none;">
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<i class="fa fa-fw fa-chart-line" style="color:var(--col_green_10);"></i>
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</td>
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<td style="border: none;">
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Traditional point forecasts are inadequate for modern energy markets with increasing uncertainty
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</td>
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</tr>
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<tr style="border: none;">
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<td style="vertical-align: top; border: none;">
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<i class="fa fa-fw fa-percent" style="color:var(--col_green_10);"></i>
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</td>
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<td style="border: none;">
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Risk inherently *is* a probabilistic concept
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</td>
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</tr>
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<tr style="border: none;">
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<td style="vertical-align: top; border: none;">
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<i class="fa fa-fw fa-dice" style="color:var(--col_green_10);"></i>
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</td>
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<td style="border: none;">
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**Probabilistic forecasting** essential for risk management, planning and decision making in volatile energy environments
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</td>
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</tr>
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<tr style="border: none;">
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<td style="vertical-align: top; border: none;">
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<i class="fa fa-fw fa-sync-alt" style="color:var(--col_green_10);"></i>
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</td>
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<td style="border: none;">
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**Online learning** methods needed for fast-updating models with streaming energy data
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</td>
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</tr>
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</table>
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:::
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::: {.column width="4%"}
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:::
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::: {.column width="48%"}
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:::
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::::
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## Overview of the Thesis {transition="fade" transition-speed="slow" #sec-overview}
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## Overview of the Thesis {transition="fade" transition-speed="slow" #sec-overview}
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@@ -220,7 +293,7 @@ col_yellow <- "#FCE135"
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</tr>
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</tr>
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</table>
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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
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<table style="width: 100%; border-collapse: separate; border-spacing: 0 1em; border: none;">
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<table style="width: 100%; border-collapse: separate; border-spacing: 0 1em; border: none;">
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<tr class = "greyed-out" style="border: none;">
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<tr class = "greyed-out" style="border: none;">
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@@ -283,8 +356,6 @@ col_yellow <- "#FCE135"
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## Overview
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## Overview
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:::: {.columns}
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:::: {.columns}
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::: {.column width="48%"}
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::: {.column width="48%"}
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@@ -301,7 +372,45 @@ col_yellow <- "#FCE135"
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#### Distributional Modeling and Forecasting of Natural Gas Prices
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#### Distributional Modeling and Forecasting of Natural Gas Prices
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```{r, echo=FALSE, fig.width = 12, fig.height = 6, fig.align="center"}
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:::
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::::
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:::: {.columns}
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::: {.column width="48%"}
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<center>
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<img src="assets/ondir/ondir_flow.png">
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</center>
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Reduces estimation time by 2-3 orders of magnitude
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Maintainins competitive forecasting accuracy
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Real-World Validation in Energy Markets
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<i class="fa-brands fa-fw fa-python" style="color: #FFD43B;"></i> Python Package ondil on <i class="fa-brands fa-fw fa-github" style="color:var(--col_grey_10);"></i> [Github](https://github.com/simon-hirsch/ondil) and [PyPi](https://pypi.org/project/ondil/)
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:::
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::: {.column width="4%"}
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:::
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::: {.column width="48%"}
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Forecasting of Day-Ahead and Month-Ahead prices
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To capture the full distribution of future prices
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Extensive data analysis from 2011-2020
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State-Space models, skewed Student's *t* distribution
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<i class="fa-brands fa-fw fa-python" style="color: #306998;"></i> Python Package *sstudentt* on <i class="fa-brands fa-fw fa-github" style="color:var(--col_grey_10);"></i> [Github](https://github.com/BerriJ/sstudentt) and [PyPi](https://pypi.org/project/sstudentt/)
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```{r, echo=FALSE, fig.width = 12, fig.height = 6, fig.align="left"}
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load("assets/ngas/residuals.RData")
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load("assets/ngas/residuals.RData")
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clr_day_ahead <- cols[5, "green"]
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clr_day_ahead <- cols[5, "green"]
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@@ -416,7 +525,7 @@ acfs_da <- pacfs %>%
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geom_line(aes(y = upper), linetype = "longdash", alpha = 0.5) +
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geom_line(aes(y = upper), linetype = "longdash", alpha = 0.5) +
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geom_line(aes(y = lower), linetype = "longdash", alpha = 0.5) +
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geom_line(aes(y = lower), linetype = "longdash", alpha = 0.5) +
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scale_color_identity() +
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scale_color_identity() +
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ylab("ACF") +
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ylab("PACF") +
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theme_minimal() +
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theme_minimal() +
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facet_grid(. ~ Var, labeller = label_parsed) +
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facet_grid(. ~ Var, labeller = label_parsed) +
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theme(
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theme(
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@@ -437,7 +546,7 @@ acfs_ma <- pacfs %>%
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geom_line(aes(y = upper), linetype = "longdash", alpha = 0.5) +
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geom_line(aes(y = upper), linetype = "longdash", alpha = 0.5) +
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geom_line(aes(y = lower), linetype = "longdash", alpha = 0.5) +
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geom_line(aes(y = lower), linetype = "longdash", alpha = 0.5) +
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scale_color_identity() +
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scale_color_identity() +
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ylab("ACF") +
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ylab("PACF") +
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theme_minimal() +
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theme_minimal() +
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scale_x_continuous(breaks = c(1, 10, 20, 30, 40)) +
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scale_x_continuous(breaks = c(1, 10, 20, 30, 40)) +
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facet_grid(. ~ Var, labeller = label_parsed) +
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facet_grid(. ~ Var, labeller = label_parsed) +
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@@ -488,6 +597,32 @@ cowplot::plot_grid(
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#### High-Resolution Peak Demand Estimation Using Generalized Additive Models and Deep Neural Networks
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#### High-Resolution Peak Demand Estimation Using Generalized Additive Models and Deep Neural Networks
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:::
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::: {.column width="4%"}
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:::
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::: {.column width="48%"}
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#### rcpptimer: Rcpp Tic-Toc Timer with OpenMP Support
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:::
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::::
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:::: {.columns}
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::: {.column width="48%"}
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Predict high-resolution electricity peaks using only low-resolution data
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Combine GAMs and DNN's for superior accuracy
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<i class="fa fa-fw fa-award" style="color:var(--col_red_9);"></i> Won Western Power Distribution Competition
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<i class="fa fa-fw fa-award" style="color:var(--col_amber_9);"></i> Won Best-Student-Presentation Award
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```{r, echo=FALSE, fig.width = 12, fig.height = 6, fig.align="center"}
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```{r, echo=FALSE, fig.width = 12, fig.height = 6, fig.align="center"}
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load("assets/minmaxload/plot_overview.rds")
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load("assets/minmaxload/plot_overview.rds")
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# linesize <- 1.2
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# linesize <- 1.2
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@@ -553,7 +688,7 @@ ggplot() +
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legend.position = "bottom",
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legend.position = "bottom",
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legend.title = element_blank(),
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legend.title = element_blank(),
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text = element_text(
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text = element_text(
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size = text_size + 2,
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size = text_size + 4,
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),
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),
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validate = FALSE
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validate = FALSE
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) +
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) +
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@@ -579,7 +714,29 @@ ggplot() +
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::: {.column width="48%"}
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::: {.column width="48%"}
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#### rcpptimer: Rcpp Tic-Toc Timer with OpenMP Support
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<i class="fa-brands fa-fw fa-r-project" style="color: #276DC3;"></i> R Package *rcpptimer* on <i class="fa-brands fa-fw fa-github" style="color:var(--col_grey_10);"></i> [Github](https://github.com/BerriJ/rcpptimer) and [CRAN](https://cran.r-project.org/web/packages/rcpptimer/)
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Provides Rcpp bindings for <i class="fa-brands fa-fw fa-github" style="color:var(--col_grey_10);"></i> [cpptimer](https://github.com/BerriJ/rcpptimer)
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tic-toc class for timing C++ code
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Supports nested, overlapping and scoped timers
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Supports OpenMP parallelism
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```c++
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//[[Rcpp::depends(rcpptimer)]]
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#include <rcpptimer.h>
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void main(){
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Rcpp::Timer timer;
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Rcpp::Timer::ScopedTimer _(timer, "ST");
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timer.tic();
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// Some more code
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timer.toc();
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} // ScopedTimer will stop automatically
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```
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