I think this is a straightforward question but I cannot seem to find the answer.
I have some mark-resighting data where most individuals (gannets) were tagged as chicks and are therefore of known age. However some were intially tagged as adults and are therefore aged 3+ at initial capture.
I wanted to set up a model where the age-specific survival part is:
for (i in 1:udot) {
for (j in first[i]:(k-1)){
S[i,j]<-s.age[age[i]+j-first[i]+1]
}}
for (y in 1:30){
s.age[y]~dbeta(1,1)
}
k is last sampling period, udot is number of individuals, first[i] is the sampling period at initial capture.
However age[i] is mostly 0, but not known for some, i.e. in the data age[i]=c(0,0,0,0,NA,0,0,0... etc)
I tried something like:
age[i]~dgamma(3,0.5)
age.use<-round(age[i])
and then modelled:
S[i,j]<-s.age[age.use[i]+j-first[i]+1]
But I get the message that age.use[1] is not data. Also, I would like to truncate the imputed ages at a minimum of 3, and a maximum of about 15....
Many thanks
Andrew
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