I am trying to use a self-defined distribution in Stan to get the parameter posterior distributions. Everything works out well except when the vector has the length 1, Stan will not work. I found some similar topics, but I don’t really understand the reason why Stan does not work in this condition. Here are my Stan code and some sample data:

```
plpstan11 = '
functions{
real nhpp_log(vector t, real beta, real theta, real tau){
real loglikelihood;
vector[num_elements(t)] loglik_part;
for (i in 1:num_elements(t)){
loglik_part[i] = log(beta) - beta*log(theta) + (beta - 1)*log(t[i]);
}
loglikelihood = sum(loglik_part) - (tau/theta)^beta;
return loglikelihood;
}
}
data {
int<lower=0> n; //total # of obs
real<lower=0> tau;//truncated time
vector<lower=0>[n] t; //failure time
}
parameters{
real<lower=0> beta;
real<lower=0> theta;
}
model{
t ~ nhpp(beta, theta, tau);
//PRIORS
beta ~ gamma(1, 1);
theta ~ gamma(1, 0.01);
}
'
library(rstan)
stan_yes = list(n = 6, tau = 657, t = c(251, 397, 406, 451, 465, 593))
stan_no = list(n = 1, tau = 657, t = 253))
fitplp <- stan(
model_code=plpstan11, model_name="NHPP", data=stan_no,
iter=1000,warmup = 500, chains=1, seed = 123
)
```

The stan code will work out well if the length of t is more than 1 (using the data `stan_yes`

). However, Stan will report the following error message only if t is a vector with length 1 (using the data `stan_no`

):

Error in new_CppObject_xp(fields$.module, fields$.pointer, …) :

Exception: mismatch in number dimensions declared and found in context; processing stage=data initialization; variable name=t; dims declared=(1); dims found=() (in ‘model352055946207_NHPP’ at line 16)

failed to create the sampler; sampling not done

I found two similar posts here:

- https://groups.google.com/forum/#!topic/stan-users/TI9S0q4h1hs
- Exception: mismatch in number dimensions declared

But from my limited understanding, none of them clearly explain the mechanism behind this error. Could anyone explain this error? Thank you!