/* Dirichlet posterior probabilities (covers BDe and K2 scores). */
double dirichlet_node(SEXP target, SEXP x, SEXP data, SEXP iss, SEXP prior,
SEXP beta, SEXP experimental, int sparse, int debuglevel) {
char *t = (char *)CHAR(STRING_ELT(target, 0));
double prob = 0, prior_prob = 0;
SEXP nodes, node_t, data_t, exp_data, parents, parent_vars, config;
/* get the node cached information. */
nodes = getListElement(x, "nodes");
node_t = getListElement(nodes, t);
/* get the parents of the node. */
parents = getListElement(node_t, "parents");
/* extract the node's column from the data frame. */
data_t = c_dataframe_column(data, target, TRUE, FALSE);
/* extract the list of eperimental data. */
exp_data = c_dataframe_column(experimental, target, TRUE, FALSE);
/* compute the prior probability component for the node. */
prior_prob = graph_prior_prob(prior, target, node_t, beta, debuglevel);
if (length(parents) == 0) {
prob = dpost(data_t, iss, exp_data);
}/*THEN*/
else {
/* generate the configurations of the parents. */
PROTECT(parent_vars = c_dataframe_column(data, parents, FALSE, FALSE));
PROTECT(config = c_configurations(parent_vars, TRUE, !sparse));
/* compute the marginal likelihood. */
prob = cdpost(data_t, config, iss, exp_data);
UNPROTECT(2);
}/*ELSE*/
if (debuglevel > 0) {
Rprintf(" > (log)prior probability is %lf.\n", prior_prob);
Rprintf(" > (log)posterior density is %lf.\n", prob);
}/*THEN*/
/* add the (log)prior to the marginal (log)likelihood to get the (log)posterior. */
prob += prior_prob;
return prob;
}/*DIRICHLET_NODE*/
double loglik_dnode(SEXP target, SEXP x, SEXP data, double *nparams, int debuglevel) {
double loglik = 0;
char *t = (char *)CHAR(STRING_ELT(target, 0));
SEXP nodes, node_t, parents, data_t, parent_vars, config;
/* get the node cached information. */
nodes = getListElement(x, "nodes");
node_t = getListElement(nodes, t);
/* get the parents of the node. */
parents = getListElement(node_t, "parents");
/* extract the node's column from the data frame. */
PROTECT(data_t = c_dataframe_column(data, target, TRUE, FALSE));
if (length(parents) == 0) {
loglik = dlik(data_t, nparams);
}/*THEN*/
else {
/* generate the configurations of the parents. */
PROTECT(parent_vars = c_dataframe_column(data, parents, FALSE, FALSE));
PROTECT(config = c_configurations(parent_vars, TRUE, TRUE));
/* compute the log-likelihood. */
loglik = cdlik(data_t, config, nparams);
UNPROTECT(2);
}/*ELSE*/
if (debuglevel > 0)
Rprintf(" > loglikelihood is %lf.\n", loglik);
UNPROTECT(1);
return loglik;
}/*LOGLIK_DNODE*/
