R 滑板成分的估算

我正在尝试调整贝叶斯层次模型

model {
  for (i in 1:n){
    y[i] ~ dpois (lambda[i])
    lambda[i] <- exp(mu+b.species[Species_A[i]] + epsilon[i])
    epsilon[i]  ~ dnorm (0, tau.epsilon)
  }
  mu ~ dnorm (0, .0001)
  mu.adj <- mu +  mean(b.species[])
  tau.epsilon <- pow(sigma.epsilon, -2)
  sigma.epsilon ~ dunif (0, 100)
  b.species[1] <-0 

  for (j in 2:n.species_A){
    b.species[j] ~ dnorm (0, tau.species)
  }
  tau.species <- pow(sigma.species, -2)
  sigma.species ~ dunif (0, 100)
}

数据如下：

n.species_A <- 3

n <- 54

species_A <- c("RJC”, “RJE”, “RJH”, “RJC”, “RJE”, “RJH”, “RJC”, “RJE”, “RJH”, “RJC”, “RJE”, “RJH”, “RJC”, “RJE”, “RJH”, “RJC", "RJE”, “RJH”, “RJC”, “RJE”, “RJH”, “RJC”, “RJE”, “RJH”, “RJC”, “RJE”, “RJH”, “RJC”, “RJE”, “RJH”, “RJC”, “RJE", "RJH”, “RJC”, “RJE”, “RJH”, “RJC”, “RJE”, “RJH”, “RJC”, “RJE”, “RJH”, “RJC”, “RJE”, “RJH”, “RJC”, “RJE”, “RJH", "RJC”, “RJE”, “RJH”, “RJC”, “RJE”, “RJH")

y_A <- c(6.80,10.20 124.20, 6.350, 0.00,63.20, 0.00, 0.00,86.850, 3.60, 2.550,60.950,0.00, 0.00,87.20, 2.60, 0.00,58.10, 3.360,34.990,62.140, 0.00, 0.00,63.90,0.00, 0.00 112.660, 0.00, 0.00 121.630, 0.00, 3.580 101.770, 0.00, 0.00 158.00,0.00, 0.00 123.279, 0.00, 0.00 124.255, 3.170, 0.00,27.840, 5.930, 0.00 174.435,0.00, 0.00,53.525, 0.00, 4.858,68.945)

使用r2winbug

skate.4 <- bugs (skateA.data, inits=skatesA.inits, skateA.parameters, model1.file, n.chains=1, n.iter=50, bugs.directory="C:/Program Files (x86)/OpenBUGS/OpenBUGS323/", program=c("OpenBUGS"), debug=TRUE)

skateA.data <- list(n=length(y_A), y_A =y_A, Species_A= Species_A, n.species_A=n.species_A)

skateA.parameters <- c ("mu","b.species", "sigma.species",  "sigma.epsilon")

但我无法运行它 在我的一些试验中，我尝试了以下缩写

skatesA.inits <- function (){
  list (mu=rnorm(0.5),  b.species=rnorm(0.2), sigma.species=runif(1),
        sigma.epsilon=runif(1))}

有人能帮我吗？ 谢谢 艾文