我对 JAGS 和贝叶斯统计非常陌生,并且一直在尝试遵循 Crawley 第 2 版 R 书中关于贝叶斯统计的第 22 章。我完全按照书中简单线性模型的代码复制代码:growth = a + b *tannin,其中有 9 行两个连续变量:增长和单宁。数据和包是这样的:
install.packages("R2jags")
library(R2jags)
growth <- c(12,10,8,11,6,7,2,3,3)
tannin <- c(0,1,2,3,4,5,6,7,8)
N <- c(1,2,3,4,5,6,7,8,9)
bay.df <- data.frame(growth,tannin,N)
ASCII 文件如下所示:
model{
for(i in 1:N) {
growth[i] ~ dnorm(mu[i],tau)
mu[i] <- a+b*tannin[i]
}
a ~ dnorm(0.0, 1.0E-4)
b ~ dnorm(0.0, 1.0E-4)
sigma <- 1.0/sqrt(tau)
tau ~ dgamma(1.0E-3, 1.0E-3)
}
但是,当我使用这段代码时:
> practicemodel <- jags(data=data.jags,parameters.to.save = c("a","b","tau"),
+ n.iter=100000, model.file="regression.bugs.txt", n.chains=3)
我收到一条错误消息,上面写着:
module glm loaded
Compiling model graph
Resolving undeclared variables
Deleting model
Error in jags.model(model.file, data = data, inits = init.values, n.chains = n.chains, :
RUNTIME ERROR:
Non-conforming parameters in function :