RStan でカテゴリカル変数の単回帰2

data {
  int N;
  int K;
  matrix[N,K] X;
  vector[N] y;
}

parameters{
  
  real a;
  vector[K] b;
  real<lower=0> sigma;
  //vector<lower=0>[K] sigma2;
  real<lower=0>[K] sigma2;
}

transformed parameters{
  vector[N] mu;
  mu=X*b+a;
 // mu=X*b;
  
  
  
}

model{
  //b ~ normal(0,sigma2);
  b ~ double_exponential(0,sigma2);
  //b ~ double_exponential(0,sigma2);
  y ~ normal(mu,sigma); 
}
 x<-tmp3[,5]
X<-dummy(x)
y<-as.numeric(tmp3[,1])
tmp<-list(x=X,y=y,N=length(x),K=length(table(x)))
 fit<-stan(file="test0_lm2.stan",data=tmp,seed=1235,chains=2)
ms<-extract(fit)

 plot(factor(names(X[1,])),apply(ms$b,2,mean),ylim=c(-30,30))
 points(factor(names(X[1,])),apply(ms$b,2,function(x){quantile(x,0.9)}),col=2)
 points(factor(names(X[1,])),apply(ms$b,2,function(x){quantile(x,0.1)}),col=2)
 names(X[1,])
  abline(h=0,lty=2)
data.frame(factor(names(X[1,])),apply(ms$b,2,mean),apply(ms$b,2,function(x){quantile(x,0.1)}),apply(ms$b,2,function(x){quantile(x,0.9)}))