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---
title: "R Notebook"
output: html_notebook
---

```{r}
library(rstan)
options(mc.cores = parallel::detectCores())
library(bayesplot)
```

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library(ggplot2)
library(palmerpenguins)

point_plot <- function(d, x, y) {
  ggplot(d) +
    geom_point(aes(x = .data[[x]], y = .data[[y]]))
}

(var_names <- colnames(penguins))

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---
title: "R Notebook"
output: html_notebook
---

## Fitting truncated and censored data to Weibull distribution

Supposing tree diameter data, fitting truncated and censored data to Weibull distribution.

See Chapter 4 [Truncated or Censored Data](https://mc-stan.org/docs/2_28/stan-users-guide/truncated-or-censored-data.html) in the Stan User's Guide.

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# 『たのしいベイズモデリング2』第5章のRコード
# CmdStanR版
# R 4.3.1 Mac, Stan 2.23.2, CmdStanR 0.5.3 で動作確認

library(readxl)
library(dplyr)
library(cmdstanr)
options(mc.cores = parallel::detectCores())

# データファイルのURL

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library(sf)
library(tmap)

# 参考にしたところ
# https://qiita.com/ocean_f/items/700aff67f3e35266b0fe

# 国土数値情報からデータをダウンロード
# https://nlftp.mlit.go.jp/ksj/gml/datalist/KsjTmplt-N03-v3_1.html
datafile <- file.path("data", "N03-20230101_01_GML",
                      "N03-23_01_230101.geojson")

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---
title: "R Notebook"
output: html_notebook
---

```{r setup}
library(ggplot2)
library(cmdstanr)

## Lotka-Volterra competitive equation

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---
title: "Zero-inflated beta regression"
output: html_notebook
---

## Setup

```{r setup}
library(ggplot2)
library(zoib)

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---
title: "Beta regression"
output: html_notebook
---

## Setup

```{r setup}
library(ggplot2)
library(betareg)

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# 経県値マップ*1をプロットするRスクリプト
# *1 https://uub.jp/j.cgi/

library(NipponMap)
library(stringr)

col_map <- c("white", "cyan", "yellowgreen", "yellow", "red", "purple")

# MAPの値は、都道府県コードの順にスコアを並べたものになります。

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---
title: "R Notebook"
output: html_notebook
---

## An example of likelihood ratio tests in R

```{r setup}
library(lmtest)
library(palmerpenguins)