Hi

I am completely new to Stan so please bear with me:-)

I have created (and run) a model in WinBugs. Since WinBugs doesn’t cut it anymore I wish to switch to Stan. I am currently attempting to run my model in Stan.

What I have is 600 crabs that were measured (length=L0) and thrown back in the sea. These crabs have been recaptured 1,2 or 3 times, indicated by variable J ( J[1] = first recapture and so on). The length at recapture is L. In the model I wish to create a Von Bertalanffy growth curve based on

-length at tagging (L0)

-length at recapture (L)

-time elapsed between tagging and recapture (T).

To do so we need to estimate two parameters, Linf and k. Since we have no way of measuring the age of the individual, the age of each individual has to be estimated also.

THE CODE I USED IN WINBUGS IS:

```
{
#PROCESS
for( i in 1 : N) {
pred.L0[i]<-Linf*(1-exp(-k*(age[i]))) #predicted length at release
L0[i]~dnorm(pred.L0[i],prec.L0)
for(j in 1:J[i]){
pred.L[i,j]<-Linf*(1-exp(-k*(age[i]+ t[i,j]))) #length at jth recapture
L[i,j]~dnorm(pred.L[i,j],prec.L)
}}
#PRIORS
for( i in 1 : N) {
age[i]~dlnorm(log.centre,prec.age)
}
#HYPER PRIORS
Linf~dnorm(200,.002) #population mean
k~dbeta(1,1) #population mean
prec.L0<-1/(sd.L0*sd.L0)
sd.L0~dunif(0,100)
prec.L<-prec.L0
centre~dunif(0,200)
log.centre<-log(centre)
prec.age~dgamma(.01,.01)
p.age~dlnorm(log.centre,prec.age)
p.Linf~dnorm(200,.002)
p.k~dbeta(1,1)
}
```

STAN SCRIPT

I’ve been trying to rewrite the script and this is how far I’ve gotten

```
data {
int<lower=0> N;
int<lower=0> T;
real L0;
real L;
}
parameters{
real Linf;
real k;
real pLinf;
real pk;
real sdL0;
real centre;
real page;
real precage;
real age;
}
transformed parameters{
real logcentre;
real precL0;
real precL;
logcentre=log(centre);
precL0=1/(sdL0*sdL0);
precL=precL0;
}
model{
Linf ~ normal(200,.002);
k ~beta(1,1);
pLinf ~ normal(200,.002);
pk ~ beta(1,1);
sdL0 ~ uniform(0,100);
centre~uniform(0,200);
page~lognormal(logcentre,precage);
precage ~ gamma(.01,.01);
age~lognormal(logcentre,precage);
for (i in 1:N)
predL0[i]=Linf*(1-exp(-k*(age[i]))) //predicted length at release
L0[i]~dnorm(predL0[i],precL0[i])
for(j in 1:J[i]){
pred.L[i,j]<-Linf*(1-exp(-k*(age[i]+ t[i,j]))) //length at jth recapture
L[i,j]~dnorm(pred.L[i,j],prec.L)
}
```

I think I’m on my way but the following message stopped me in my track:

```
SYNTAX ERROR, MESSAGE(S) FROM PARSER:
Indexed expression must have at least as many dimensions as number of indexes supplied:
indexed expression dimensionality = 0; indexes supplied = 1
error in 'model_Growth2' at line 43, column 33
-------------------------------------------------
41:
42: for (i in 1:N)
43: predL0[i]=Linf*(1-exp(-k*(age[i]))) //predicted length at release
^
44: L0[i]~dnorm(predL0[i],precL0[i])
-------------------------------------------------
Error in stanc(model_code = paste(program, collapse = "\n"), model_name = model_cppname, :
failed to parse Stan model 'Growth2' due to the above error.
```

How do I solve this? I appreciate any help and if you see any other mistakes in my code, feel free to point them out to me:-)