bayesian_intro_stan.Rmd

# Stan入门 {#bayesian-intro-stan}


```{r, include=FALSE}
knitr::opts_chunk$set(
   echo         = TRUE, 
   warning      = FALSE, 
   message      = FALSE,
   fig.showtext = TRUE
)
```

相比于传统的方法来说，[Stan](https://mc-stan.org/)建模具有更好的可操作性、透明性和可解释性。本周开始，我们将开始学习贝叶斯数据分析，希望通过一些案例，让大家了解Stan的强大和价值。根据我有限的学习经验，采用code first 教学。



## R4.1配置方法

- 安装 [Rtools4.0](https://cran.r-project.org/bin/windows/Rtools/)到`C`盘
   
- 添加系统路径(电脑 - 属性 - 高级系统设置 - 环境变量 - 系统变量 - Path) 
  - `C:\rtools40`
  - `C:\rtools40\mingw64\bin`
  - `C:\rtools40\usr\bin`
  
- [配置](https://github.com/stan-dev/rstan/wiki/Configuring-C---Toolchain-for-Windows)
```{r, eval=FALSE}
writeLines('PATH="${RTOOLS40_HOME}\\usr\\bin;${PATH}"', con = "~/.Renviron")
```

- [安装rstan宏包](https://mc-stan.org/r-packages/)

```{r, eval=FALSE}
remove.packages(c("rstan", "StanHeaders"))
install.packages("rstan", repos = c("https://mc-stan.org/r-packages/", getOption("repos")))
install.packages(c("tidybayes", "bayesplot"))
```


## R4.2配置方法

- 安装 [Rtools42](https://cran.r-project.org/bin/windows/Rtools/rtools42/rtools.html)到`C`盘，推荐使用它默认的路径


- [安装rstan宏包](https://mc-stan.org/r-packages/)

```{r, eval=FALSE}
remove.packages(c("rstan", "StanHeaders"))
install.packages(c("rstan", "StanHeaders"), repos = c("https://mc-stan.org/r-packages/", getOption("repos")))
install.packages(c("tidybayes", "bayesplot"))
```



## 遇到问题，请参考

- <https://mc-stan.org/r-packages/>
- <https://github.com/stan-dev/rstan/wiki/RStan-Getting-Started>



```{r, echo = F, message = F, warning = F, results = "hide"}
pacman::p_unload(pacman::p_loaded(), character.only = TRUE)
```