Type objective_function<Type>::operator() () {
DATA_VECTOR(E);
DATA_VECTOR(deaths);
DATA_SPARSE_MATRIX(P); // precision matrix
PARAMETER(alpha);
PARAMETER(log_sigma2_V);
PARAMETER_VECTOR(V);
PARAMETER(log_sigma2_U);
PARAMETER_VECTOR(W);
int N = E.size();
vector<Type> log_deaths_pred(N);
vector<Type> mu(N);
Type nll = 0;
Type tau_V = 1 / exp(log_sigma2_V);
Type tau_U = 1 / exp(log_sigma2_U);
nll -= dnorm(alpha, Type(0), Type(10), 1);
nll -= dgamma(tau_V, Type(0.5), Type(2000), 1);
nll -= dgamma(tau_U, Type(0.5), Type(2000), 1);
nll -= dnorm(V, Type(0), exp(0.5 * log_sigma2_V), 1).sum();
vector<Type> tmp = P * W;
nll -= -0.5 * (W * tmp).sum();
vector<Type> U = W * exp(0.5 * log_sigma2_U);
nll -= dnorm(U.sum(), Type(0), Type(0.00001), 1);
for (size_t i = 0; i < N; i++) log_deaths_pred(i) = log(E(i)) + alpha + V(i) + U(i);
for (size_t i = 0; i < N; i++) nll -= dpois(deaths(i), exp(log_deaths_pred(i)), 1);
for (size_t i = 0; i < N; i++) mu(i) = exp(alpha + V(i) + U(i));
vector<Type> deaths_pred = exp(log_deaths_pred);
ADREPORT(U);
ADREPORT(deaths_pred);
ADREPORT(mu);
return nll;
}
Type objective_function<Type>::operator() ()
{
DATA_VECTOR (a);
DATA_ARRAY (b);
DATA_MATRIX (c);
DATA_SPARSE_MATRIX (d);
PARAMETER (p);
REPORT(a);
REPORT(b);
REPORT(c);
REPORT(d);
REPORT(p);
//// Vector of anything:
vector<matrix<Type> > voa(2);
voa[0] = c;
voa[1] = c;
REPORT(voa);
return 0;
}
