r - Fiting Weibull using R2OpenBUGS -


because estimation of parameters of weibull function using r2openbugs different amounts provided generate data set using rweibull? what's wrong fit?

data<-rweibull(200, 2, 10)  model<-function(){  v ~ dgamma(0.0001,0.0001) lambda ~ dgamma(0.0001,0.0001)  for(i in 1:n){    y[i] ~ dweib(v, lambda)    } }  y<-data n<-length(y) data<-list("y", "n")  inits<-function(){list(v=1, lambda=1)} params<-c("v", "lambda") model.file<-file.path(tempdir(), "model.txt") write.model(model, model.file) weibull<-bugs(data, inits, params, model.file, n.iter = 3000, n.burnin =  2000, n.chains = 3) print(weibull, 4)

the result obtained is:

current: 3 chains, each 3000 iterations (first 2000 discarded) cumulative: n.sims = 3000 iterations saved           mean     sd       2.5%       25%       50%       75%      97.5%    rhat     n.eff v           2.0484 0.1044    1.8450    1.9780    2.0500    2.1180    2.2470 1.0062   780 lambda      0.0097 0.0026    0.0056    0.0078    0.0093    0.0112    0.0159 1.0063   830 deviance 1145.6853 1.8403 1144.0000 1144.0000 1145.0000 1146.0000 1151.0000 1.0047   770  pd = 1.6 , dic = 1147.0

r parameterizes weibull using shape (=2 in case) , scale (=10) default: bugs uses shape , lambda, lambda=(1/scale)^shape. should expect lambda approximately (1/10)^2=0.01, close median of 0.0093.

this question on crossvalidated, , this paper in r journal, compare parameterizations.


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