Analyzing the posterior prediction samples

Modeling
6

thank you @jonah.

When I added the generated quantities and compiled the code, I get an error trying to sample. Below is the new model block.

reinstatement_model = """
data {
    int<lower=0> n; // number policy term years
    int<lower=0>  NonCatcvrcnt[n]; // claims
    vector[n] alertflag; //alert flag
}

parameters {
    real<lower=0> mu;
    real beta;

}

model {
       mu ~ normal(0,3);
       beta ~ normal(0,1);
       NonCatcvrcnt ~ poisson_log(mu + alertflag*beta);
}

generated quantities {
    int y_hat[n];
    
    for (i in 1:n){
            y_hat = poisson_log_rng(mu+alertflag*beta);
            }
    }

"""

fit = pystan.StanModel(model_code=reinstatement_model)

samples = fit.sampling(data=df_group_dict, iter = 1000,
                       chains = 4, warmup = 200, thin = 1,
                       seed = 101)

The error I get is the following?

RemoteTraceback: 
"""
Traceback (most recent call last):
  File "C:\Users\JORDAN.HOWELL.GITDIR\AppData\Local\Continuum\anaconda3\envs\stan_env\lib\multiprocessing\pool.py", line 121, in worker
    result = (True, func(*args, **kwds))
  File "C:\Users\JORDAN.HOWELL.GITDIR\AppData\Local\Continuum\anaconda3\envs\stan_env\lib\multiprocessing\pool.py", line 44, in mapstar
    return list(map(*args))
  File "stanfit4anon_model_f329bc7ad7396a8e372d31ea21f5a0f6_4091579692383103566.pyx", line 373, in stanfit4anon_model_f329bc7ad7396a8e372d31ea21f5a0f6_4091579692383103566._call_sampler_star
  File "stanfit4anon_model_f329bc7ad7396a8e372d31ea21f5a0f6_4091579692383103566.pyx", line 406, in stanfit4anon_model_f329bc7ad7396a8e372d31ea21f5a0f6_4091579692383103566._call_sampler
RuntimeError: std::bad_alloc
"""


The above exception was the direct cause of the following exception:

Traceback (most recent call last):

  File "<ipython-input-13-65ef346ba5cf>", line 3, in <module>
    seed = 101)

  File "C:\Users\JORDAN.HOWELL.GITDIR\AppData\Roaming\Python\Python37\site-packages\pystan\model.py", line 813, in sampling
    ret_and_samples = _map_parallel(call_sampler_star, call_sampler_args, n_jobs)

  File "C:\Users\JORDAN.HOWELL.GITDIR\AppData\Roaming\Python\Python37\site-packages\pystan\model.py", line 85, in _map_parallel
    map_result = pool.map(function, args)

  File "C:\Users\JORDAN.HOWELL.GITDIR\AppData\Local\Continuum\anaconda3\envs\stan_env\lib\multiprocessing\pool.py", line 268, in map
    return self._map_async(func, iterable, mapstar, chunksize).get()

  File "C:\Users\JORDAN.HOWELL.GITDIR\AppData\Local\Continuum\anaconda3\envs\stan_env\lib\multiprocessing\pool.py", line 657, in get
    raise self._value

RuntimeError: std::bad_alloc