def _get_log_density_parameters_prior( self ): precision_term = 0 location_term = 0 for genome in constants.genomes: alpha = self.parameters[genome]['alpha'] beta = self.parameters[genome]['beta'] s = alpha + beta mu = alpha / s precision_priors = self.priors[genome]['precision'] location_priors = self.priors[genome]['location'] precision_term += np.sum( log_translated_gamma_pdf( s, precision_priors['shape'], precision_priors['scale'], precision_priors['min'] ) ) location_term += np.sum( log_beta_pdf( mu, location_priors['alpha'], location_priors['beta'] ) ) return precision_term + location_term
def _get_log_density_parameters_prior( self ): log_prior = 0. for genome in constants.genomes: mu = self.parameters[genome]['mu'] alpha = self.priors[genome]['mu']['alpha'] beta = self.priors[genome]['mu']['beta'] log_prior += np.sum( log_beta_pdf( mu, alpha, beta ) ) return log_prior
def _get_log_density_parameters_prior(self): log_prior = 0.0 mu = self.parameters["mu"] alpha = self.priors["mu"]["alpha"] beta = self.priors["mu"]["beta"] log_prior += log_beta_pdf(mu, alpha, beta) log_prior = log_prior.sum() return log_prior
def _get_log_density_parameters_prior(self): alpha = self.parameters["alpha"] beta = self.parameters["beta"] s = alpha + beta mu = alpha / s precision_priors = self.priors["precision"] location_priors = self.priors["location"] precision_term = np.sum(log_gamma_pdf(s, precision_priors["shape"], precision_priors["scale"])) location_term = np.sum(log_beta_pdf(mu, location_priors["alpha"], location_priors["beta"])) return precision_term + location_term
def _get_log_density_parameters_prior(self): log_prior = 0.0 for genome in constants.genomes: mu = self.parameters[genome]["mu"] alpha = self.priors[genome]["mu"]["alpha"] beta = self.priors[genome]["mu"]["beta"] log_prior += log_beta_pdf(mu, alpha, beta) log_prior = log_prior.sum() return log_prior
def _get_log_density_parameters_prior(self): precision_term = 0 location_term = 0 for genome in constants.genomes: alpha = self.parameters[genome]["alpha"] beta = self.parameters[genome]["beta"] s = alpha + beta mu = alpha / s precision_priors = self.priors[genome]["precision"] location_priors = self.priors[genome]["location"] precision_term += np.sum( log_translated_gamma_pdf( s, precision_priors["shape"], precision_priors["scale"], precision_priors["min"] ) ) location_term += np.sum(log_beta_pdf(mu, location_priors["alpha"], location_priors["beta"])) return precision_term + location_term