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stanhour6.Rmd
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---
title: "Stan @ ISEC 2020"
subtitle: ""
author: "The Crew"
date: "20 June 2020"
output:
xaringan::moon_reader:
css: xaringan-themer.css
lib_dir: libs
nature:
highlightStyle: solarized-light
highlightLines: true
countIncrementalSlides: false
---
class: inverse, center, middle
```{r setup, include=FALSE}
options(htmltools.dir.version = FALSE)
library(ggplot2)
```
```{r xaringan-themer, include=FALSE, warning=FALSE}
library(xaringanthemer)
style_solarized_light()
```
# Statistical Models
---
## Model Checking:
-- `Residuals`
-- `Prior Predictive Checks`
-- `Posterior Predictive Checks`
-- `Predictive Accuracy`
---
class: inverse, middle
# Statistical Model Assessment $\neq$ (Biologically) Useful Model
---
class: inverse
#Biological Realism
`In what manner does my model represent biologically/ecologically important features, and where does it fail?`
---
---
### Interpreting the Statistical Results...
...by the data that your model generates.
In particular, pretend each realization is something that actually occurred, does it make sense? Generate a population/group/system, where does your model fail?
--
### Challenge
Make your model stand out by inserting **at least 1** structure that is specific to your system.
--
Yes, even with a GLM. Even a linear model.
---
class: inverse, middle
## Embrace Your Domain Expertise
**it's the most important part of the story!**
---
### Stan Help/Advice
https://discourse.mc-stan.org/
---
class: inverse, center
### Stan Ecology Community
https://stanecology.github.io
