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ESA_slidedeck.Rmd

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---
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title: "Ecological Time Series Analysis and Forecasting in R"
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title: "Ecological Time Series Analysis and Forecasting"
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institute: "School of Veterinary Science, University of Queensland, Australia"
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author: "Nicholas Clark"
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date: "Friday 13th December, 2024"
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Press the "o" key on your keyboard to navigate among html slides
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Access the [workshop materials here](https://github.com/nicholasjclark/ESA_2024_timeseries)
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- View the sample `R` scripts in [live_code_examples](https://github.com/nicholasjclark/ESA_2024_timeseries/tree/main/live_code_examples)
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- View the sample `r fontawesome::fa("r-project", fill = "steelblue")` scripts in [live_code_examples](https://github.com/nicholasjclark/ESA_2024_timeseries/tree/main/live_code_examples)
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- Use the [Google Doc](https://docs.google.com/document/d/1xd3icf1wxGxO3SVt2AmKO8CkeKv1QpsxgqK7rR15U08/edit?tab=t.0#heading=h.ds87nag4ykyb) to ask questions
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Relevant open-source materials include:
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\begin{align*}
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Y_t & \sim Normal(\alpha + \sum_{j=1}^{J}(\beta_j x_{jt}) + Zz_t, \sigma_y) \\
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z_t & \sim Normal(\sum_{k=1}^{K}(\beta_k q_{kt}), \sigma_z)
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z_t & \sim Normal(f(z_{t-lag}) + \sum_{k=1}^{K}(\beta_k q_{kt}), \sigma_z)
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\end{align*}
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\begin{align*}
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\mathbb{E}(\boldsymbol{Y_t}|\boldsymbol{X_t}, \boldsymbol{Q_t}) & = g^{-1}(\alpha + \sum_{j=1}^{J}f(x_{jt}) + Zz_t) \\
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z_t & \sim Normal(\sum_{k=1}^{K}f(q_{kt}), \sigma_z)
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z_t & \sim Normal(f(z_{t-lag}) + \sum_{k=1}^{K}f(q_{kt}), \sigma_z)
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\end{align*}
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## Produce all `Stan` code and objects
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```{r eval=FALSE}
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code(model)
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stancode(model)
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```
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.small[
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```{r echo=FALSE}
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class: inverse middle center big-subsection
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# Live code example
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# Live code examples

ESA_slidedeck.html

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<!DOCTYPE html>
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<html lang="" xml:lang="">
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<head>
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<title>Ecological Time Series Analysis and Forecasting in R</title>
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<title>Ecological Time Series Analysis and Forecasting</title>
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<meta charset="utf-8" />
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<meta name="author" content="Nicholas Clark" />
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<script src="libs/header-attrs/header-attrs.js"></script>
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class: inverse, middle, left, my-title-slide, title-slide
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.title[
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# Ecological Time Series Analysis and Forecasting in R
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# Ecological Time Series Analysis and Forecasting
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]
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.author[
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### Nicholas Clark
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Press the "o" key on your keyboard to navigate among html slides
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Access the [workshop materials here](https://github.com/nicholasjclark/ESA_2024_timeseries)
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- View the sample `R` scripts in [live_code_examples](https://github.com/nicholasjclark/ESA_2024_timeseries/tree/main/live_code_examples)
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- View the sample <svg aria-hidden="true" role="img" viewBox="0 0 581 512" style="height:1em;width:1.13em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:steelblue;overflow:visible;position:relative;"><path d="M581 226.6C581 119.1 450.9 32 290.5 32S0 119.1 0 226.6C0 322.4 103.3 402 239.4 418.1V480h99.1v-61.5c24.3-2.7 47.6-7.4 69.4-13.9L448 480h112l-67.4-113.7c54.5-35.4 88.4-84.9 88.4-139.7zm-466.8 14.5c0-73.5 98.9-133 220.8-133s211.9 40.7 211.9 133c0 50.1-26.5 85-70.3 106.4-2.4-1.6-4.7-2.9-6.4-3.7-10.2-5.2-27.8-10.5-27.8-10.5s86.6-6.4 86.6-92.7-90.6-87.9-90.6-87.9h-199V361c-74.1-21.5-125.2-67.1-125.2-119.9zm225.1 38.3v-55.6c57.8 0 87.8-6.8 87.8 27.3 0 36.5-38.2 28.3-87.8 28.3zm-.9 72.5H365c10.8 0 18.9 11.7 24 19.2-16.1 1.9-33 2.8-50.6 2.9v-22.1z"/></svg> scripts in [live_code_examples](https://github.com/nicholasjclark/ESA_2024_timeseries/tree/main/live_code_examples)
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- Use the [Google Doc](https://docs.google.com/document/d/1xd3icf1wxGxO3SVt2AmKO8CkeKv1QpsxgqK7rR15U08/edit?tab=t.0#heading=h.ds87nag4ykyb) to ask questions
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Relevant open-source materials include:
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`\begin{align*}
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Y_t &amp; \sim Normal(\alpha + \sum_{j=1}^{J}(\beta_j x_{jt}) + Zz_t, \sigma_y) \\
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z_t &amp; \sim Normal(\sum_{k=1}^{K}(\beta_k q_{kt}), \sigma_z)
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z_t &amp; \sim Normal(f(z_{t-lag}) + \sum_{k=1}^{K}(\beta_k q_{kt}), \sigma_z)
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\end{align*}`
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`\begin{align*}
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\mathbb{E}(\boldsymbol{Y_t}|\boldsymbol{X_t}, \boldsymbol{Q_t}) &amp; = g^{-1}(\alpha + \sum_{j=1}^{J}f(x_{jt}) + Zz_t) \\
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z_t &amp; \sim Normal(\sum_{k=1}^{K}f(q_{kt}), \sigma_z)
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z_t &amp; \sim Normal(f(z_{t-lag}) + \sum_{k=1}^{K}f(q_{kt}), \sigma_z)
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\end{align*}`
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## Produce all `Stan` code and objects
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```r
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code(model)
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stancode(model)
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```
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.small[
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class: inverse middle center big-subsection
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# Live code example
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# Live code examples
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</textarea>
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<style data-target="print-only">@media screen {.remark-slide-container{display:block;}.remark-slide-scaler{box-shadow:none;}}</style>
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<script src="https://remarkjs.com/downloads/remark-latest.min.js"></script>

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