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
