如何matlab中用winbugs

如何matlab中用winbugs

语法及Prior distributions有错的地方,
都已帮你更正.
A2=0,表示有误,请自行更改.
运行结果如下:

Inference for Bugs model at "rabbit.bug", fit using WinBUGS,
1 chains, each with 13000 iterations (first 3000 discarded)
n.sims = 10000 iterations saved
mean sd 2.5% 25% 50% 75% 97.5%
a 1.001 0.001 1.000 1.000 1.000 1.001 1.002
b 4.979 0.021 4.924 4.971 4.985 4.994 5.000
p 4.976 0.025 4.911 4.966 4.983 4.993 4.999
q 3.002 0.002 3.000 3.001 3.002 3.003 3.008
k 1.002 0.002 1.000 1.001 1.001 1.003 1.007
logl -1876.811 2.236 -1882.000 -1878.000 -1876.000 -1875.000 -1873.000
A2 0.000 0.000 0.000 0.000 0.000 0.000 0.000
deviance 5227.280 4.458 5221.000 5224.000 5227.000 5230.000 5238.000
DIC info (using the rule, pD = Dbar-Dhat)
pD = 0.0 and DIC = 5227.3
DIC is an estimate of expected predictive error (lower deviance is better).
Ps:
Prior distributions dunif()
的范围请自行更改决定
以上仅供参考
rabbit.bug

以下例子有如何用r调用winbugs，如果是openbugs需要加载另外一个包 > # r code with interface to winbugs > > library(r2winbugs) > y<-read.table("d:/bugs/jump.dat",header=true) #import data# > n<-length(y) > xi0<-rep(0,n) # give initial values to state variables# > j0<-rep(0,n) > data<-list("n","y") > # give initial values to the parameters for winbugs # > inits <-function() {list ( tau=2, + jtau=2, + mu=0, + jmu=0, + lamda = 0.05, xi=xi0,j=j0)} > parameters<- c("sigma","jsigma","mu","jmu","lamda","xi","j") > # quote the winbugs# > jump.sim<-bugs (data, inits=inits, parameters, "model.bug", n.chains=3, n.iter=1000,debug=true, + dic=true,bugs.directory = "d:/program files/winbugs14/",working.directory = "d:/bugs") 错误于is.finite(x) : 没有为'list'类型实现默认的方法