kosugitti

#!/usr/bin/bash
#####################################################################text1
## changePath
path="course_materials/tex"
filename="Dkiso1_book"
cd $path
## backup
cp ${filename}.tex ${filename}.old
########### upgrade patch
val=$(sed -n 4p ${filename}.tex )

kosugitti

library(rstan)
rstan_options(auto_write = TRUE)
options(mc.cores = parallel::detectCores())

stancode <- "
data {
  int<lower=0> J; // number of schools 
  real y[J]; // estimated treatment effects
  real<lower=0> sigma[J]; // s.e. of effect estimates 
}

kosugitti

A <- factor(rep(1:2,each=8),labels=LETTERS[1:2])
B <- factor(rep(rep(1:4,each=2),2),labels=letters[1:4])
C <- factor(rep(1:2,8),labels=c("あ","い"))
dat <- data.frame(A,B,C)
dat$val <- rnorm(16,0,1)


library(tidyverse)           
dat %>% group_by(A,B) %>% summarise(means=mean(val))

kosugitti

a <- 1.5
d <-  c(-1.5,0,1)
K <- 3

pjkt <- function(theta,a,d,k,K){
  bunbo <- 0.0
  for(m in 0:K){
    tmp <- 0.0
    for(l in 0:m){
      if(l!=0){

kosugitti

model <- '
parameters {
  vector[2] z;
}

model{
  matrix[2,2] sigma;
  vector[2] mu;

  mu[1] <- 0.0;

kosugitti

library(rstan)
rstan_options(auto_write = TRUE)
options(mc.cores = parallel::detectCores())
model <- '
data{
  int<lower=0> N1;
  int<lower=0> N2;
  int<lower=0> N3;
  real y1[N1];
  real y2[N2];

kosugitti

## 2016年度の不倫報道データ
dataset <- as.data.frame(
matrix(c("ベッキー","2016-01-07",
         "狩野英孝","2016-02-03",
         "宮崎謙介議員","2016-02-10",
         "桂文枝","2016-03-16",
         "石井竜也","2016-03-17",
         "乙武洋匡","2016-03-23",
         "とにかく明るい安村","2016-04-01",
         "NMB48木下春奈","2016-05-08",

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---
title: "心理学統計法レポート課題2016"
output:
  bookdown::pdf_book:
    toc: false
    latex_engine: xelatex
mainfont: Hiragino Kaku Gothic Pro
---

\begin{center}

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data{
  int N;
  vector[N] X;
  vector[N] Y;
}
parameters{
  real alpha;
  real beta;
  real<lower=0> sigma;
}

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data{
  int<lower=0> N1;
  int<lower=0> N2;
  real X1[N1];
  real X2[N2];
}
parameters{
  real mu1;
  real mu2;
  real<lower=0> sigma1;