CS计算机代考程序代写 chain rm(list=ls()); set.seed(20210323);

rm(list=ls()); set.seed(20210323);

# filename <- "~/Bayes/Data/schools_data.txt" # schools <- read.table(file=filemane, header=T, sep=",") # rm(filename) J <- 8 # J <- nrow(schools) y <- c(28,8,-3,7,-1,1,18,12) # y <- schools$estimate sigma <- c(15,10,16,11,9,11,10,18) # sigma <- schools$sd library("rstan") stan_model <- " data{ int J;
real y[J];
real sigma[J];
}

parameters{
real mu;
real tau;
vector[J] theta;
}

model{
theta ~ normal(mu, tau);
y ~ normal(theta, sigma);
}
”

schools_fit <- stan(model_code=stan_model, data=c("J", "y", "sigma"), iter=1000, chains=4) print(schools_fit) plot(schools_fit) summary(schools_fit)$summary schools_sim <- extract(schools_fit) names(schools_sim)