Currently going through examples volume 1 and came across an error with the dyes example.
When I try to load inits from the example it returns "this chain contains uninitialized variables. I am not sure which part of it is not right as on the first sight I see theta, tau.btw and tau.with is all specified and nothing is left out.
I am using the code directly from Examples Vol 1 under help tab. The same error happened to all three choices of priors for between-variation.
I would really appreciate any advice on the problem. Thanks in advance.
Below is the code I copied directly from the dyes example.
model
{
for( i in 1 : batches ) {
mu[i] ~ dnorm(theta, tau.btw)
for( j in 1 : samples ) {
y[i , j] ~ dnorm(mu[i], tau.with)
}
}
theta ~ dnorm(0.0, 1.0E-10)
# prior for within-variation
sigma2.with <- 1 / tau.with
tau.with ~ dgamma(0.001, 0.001)
# Choice of priors for between-variation
# Prior 1: uniform on SD
#sigma.btw~ dunif(0,100)
#sigma2.btw<-sigma.btw*sigma.btw
#tau.btw<-1/sigma2.btw
# Prior 2: Uniform on intra-class correlation coefficient,
# ICC=sigma2.btw / (sigma2.btw+sigma2.with)
ICC ~ dunif(0,1)
sigma2.btw <- sigma2.with *ICC/(1-ICC)
tau.btw<-1/sigma2.btw
# Prior 3: gamma(0.001, 0.001) NOT RECOMMENDED
#tau.btw ~ dgamma(0.001, 0.001)
#sigma2.btw <- 1 / tau.btw
}
Data
list(batches = 6, samples = 5,
y = structure(
.Data = c(1545, 1440, 1440, 1520, 1580,
1540, 1555, 1490, 1560, 1495,
1595, 1550, 1605, 1510, 1560,
1445, 1440, 1595, 1465, 1545,
1595, 1630, 1515, 1635, 1625,
1520, 1455, 1450, 1480, 1445), .Dim = c(6, 5)))
Inits1
list(theta=1500, tau.with=1, sigma.btw=1)
Inits2
list(theta=1500, tau.with=1,ICC=0.5)
Inits3
list(theta=1500, tau.with=1, tau.btw=1)
That is not an error per se. Yes you have provided the inits for the parameters of interest. However there are the six
mu[i]variables that are not data, but are variables drawn frommu[i] ~ dnorm(theta, tau.btw).You could provide initial values for these as well, but it is best imo to just click on
gen initsif you are using WinBUGS from the GUI - this will provide initial values for those.