proto_model::proto_model(ast_manager & m, simplifier & s, params_ref const & p):
model_core(m),
m_asts(m),
m_simplifier(s),
m_afid(m.mk_family_id(symbol("array"))) {
register_factory(alloc(basic_factory, m));
m_user_sort_factory = alloc(user_sort_factory, m);
register_factory(m_user_sort_factory);
m_model_partial = model_params(p).partial();
}
//' Generate Latent Time Series based on Model (Internal)
//'
//' Create a latent time series based on a supplied time series model.
//' @param N An \code{interger} containing the amount of observations for the time series.
//' @param theta A \code{vec} containing the parameters to use to generate the model.
//' @param desc A \code{vector<string>} containing the different model types (AR1, WN, etc..).
//' @param objdesc A \code{field<vec>} containing the different model objects e.g. AR1 = c(1,1)
//' @return A \code{mat} containing data for each decomposed and combined time series.
//' @backref src/gen_process.cpp
//' @backref src/gen_process.h
//' @keywords internal
//' @examples
//' # AR
//' set.seed(1336)
//' gen_lts(10, c(.9,1), "AR1", list(c(1,1)))
// [[Rcpp::export]]
arma::mat gen_lts(unsigned int N, const arma::vec& theta, const std::vector<std::string>& desc, const arma::field<arma::vec>& objdesc){
unsigned int i_theta = 0;
unsigned int num_desc = desc.size();
arma::mat x = arma::zeros<arma::mat>(N, num_desc+1);
for(unsigned int i = 0; i < num_desc; i++){
double theta_value = theta(i_theta);
std::string element_type = desc[i];
// AR 1
if(element_type == "AR1" || element_type == "GM"){
// First value is phi, increment for sigma2
++i_theta;
// Get sigma2, this increment is taken care of at the end.
double sig2 = theta(i_theta);
// Compute theoretical WV
// Store it into cube x
x.col(i) = gen_ar1(N, theta_value, sig2);
x.col(num_desc) += x.col(i);
}
// WN
else if(element_type == "WN") {
x.col(i) = gen_wn(N, theta_value);
x.col(num_desc) += x.col(i);
}
// DR
else if(element_type == "DR"){
x.col(i) = gen_dr(N, theta_value);
x.col(num_desc) += x.col(i);
}
// QN
else if(element_type == "QN"){
x.col(i) = gen_qn(N, theta_value);
x.col(num_desc) += x.col(i);
}
// RW
else if(element_type == "RW"){
x.col(i) = gen_rw(N, theta_value);
x.col(num_desc) += x.col(i);
}
// ARMA
else {
// Unpackage ARMA model parameter
arma::vec model_params = objdesc(i);
// Get position numbers (AR,MA,SIGMA2)
unsigned int p = model_params(0);
unsigned int q = model_params(1);
// Set up temp storage
arma::vec ar;
arma::vec ma;
// Get AR values
if(p == 0){
ar = arma::zeros<arma::vec>(0);
}else{
ar = theta.rows(i_theta,i_theta+p-1);
}
// Account for the number of P values
i_theta += p;
// Get MA values
if(q == 0){
ma = arma::zeros<arma::vec>(0);
}else{
ma = theta.rows(i_theta,i_theta+q-1);
}
// Account for Q values
i_theta += q;
// Extract sigma2
double sig2 = theta(i_theta);
// Modified arima.sim
x.col(i) = gen_arma(N, ar, ma, sig2, 0);
x.col(num_desc) += x.col(i);
}
// Increment theta once to account for popped value
++i_theta;
}
return x;
}