biogeme.latent_variables.positive_parameter_factory module

Factory utilities for strictly positive parameters.

This module provides a generic mechanism to define positive model parameters in a way that is compatible with both maximum likelihood and Bayesian estimation.

In a maximum likelihood context, positivity is typically enforced by estimating the logarithm of the parameter and exponentiating it. This avoids explicit constraints and generally improves numerical stability.

In a Bayesian context, it is often preferable to work directly with the parameter itself and impose positivity through a lower bound set to a small positive value. This leads to more interpretable posterior draws and avoids artificial symmetry in the parameter space.

The use of factories abstracts away these implementation details: components that rely on positive parameters do not need to know whether a log-transformed or directly constrained representation is used.

class biogeme.latent_variables.positive_parameter_factory.PositiveParameterFactory(*args, **kwargs)

Bases: Protocol

Protocol for factories creating strictly positive model parameters.

Implementations return a Biogeme Expression representing a parameter constrained to be strictly positive.

class biogeme.latent_variables.positive_parameter_factory.SigmaFactory(*args, **kwargs)

Bases: Protocol

Protocol for factories creating strictly positive sigma (scale) parameters.

biogeme.latent_variables.positive_parameter_factory.make_positive_parameter_factory(*, use_log)

Create a factory for strictly positive parameters.

Two parameterizations are supported:

• If use_log is True, the returned factory creates an unconstrained parameter in log-space (named "<prefix>_<name>_log") and returns its exponential. This is typically used for maximum-likelihood estimation.

• If use_log is False, the returned factory creates a directly constrained parameter (named "<prefix>_<name>") with a lower bound set to SMALL_POSITIVE. This is typically used for Bayesian estimation.

Parameters:

use_log (bool) – If True, define parameters in log-space and exponentiate them.

Return type:

PositiveParameterFactory

Returns:

A callable factory compatible with PositiveParameterFactory.

biogeme.latent_variables.positive_parameter_factory.make_sigma_factory(*, use_log)

Create a sigma factory (specialization of the positive-parameter factory).

The sigma factory creates a strictly positive scale parameter named "<prefix>_sigma" (or "<prefix>_sigma_log" in log-space) using the same parameterization rules as make_positive_parameter_factory().

Parameters:

use_log (bool) – If True, define sigma in log-space and exponentiate it.

Return type:

SigmaFactory

Returns:

A callable factory compatible with SigmaFactory.