void BasicSkewGenerator::UpdateSkewGenerator(ShortStack &total_theory) {
// put everything to null
ResetUpdate();
//for (unsigned int i_read=0; i_read<total_theory.my_hypotheses.size(); i_read++){
for (unsigned int i_ndx = 0; i_ndx < total_theory.valid_indexes.size(); i_ndx++) {
unsigned int i_read = total_theory.valid_indexes[i_ndx];
AddCrossUpdate(total_theory.my_hypotheses[i_read]);
}
DoLatentUpdate(); // new latent predictors for sigma
}
// important: residuals need to be reset before this operation
void BasicBiasGenerator::UpdateBiasGenerator(ShortStack &my_theory) {
ResetUpdate();
//for (unsigned int i_read=0; i_read<total_theory.my_hypotheses.size(); i_read++){
for (unsigned int i_ndx = 0; i_ndx < my_theory.valid_indexes.size(); i_ndx++) {
unsigned int i_read = my_theory.valid_indexes[i_ndx];
AddCrossUpdate(my_theory.my_hypotheses[i_read]);
}
DoUpdate(); // new bias estimated
//cout << "Bias " << bias_generator.latent_bias[0] << "\t" << bias_generator.latent_bias[1] << endl;
}
// important: residuals do not need to be reset before this operation (predictions have been corrected for bias already)
void BasicSigmaGenerator::UpdateSigmaGenerator(ShortStack &total_theory) {
// put everything to null
ResetUpdate();
// float k_zero = 1.0f;
for (unsigned int i_ndx = 0; i_ndx < total_theory.valid_indexes.size(); i_ndx++) {
unsigned int i_read = total_theory.valid_indexes[i_ndx];
AddCrossUpdate(total_theory.my_hypotheses[i_read]);
}
// now that I've established basic weight, I can update
for (unsigned int i_ndx = 0; i_ndx < total_theory.valid_indexes.size(); i_ndx++) {
unsigned int i_read = total_theory.valid_indexes[i_ndx];
// additional variability from cluster shifting
// bayesian multidimensional normal
AddShiftCrossUpdate(total_theory.my_hypotheses[i_read], k_zero);
}
DoLatentUpdate(); // new latent predictors for sigma
}
