ConditionalRegressionMixin

class pyoptex.analysis.mixins.conditional_mixin.ConditionalRegressionMixin(*args, conditional=False, **kwargs)

Mixin to provide additional capabilities of fitting a conditional model or not. Should be used as

>>> class MyRegressor(ConditionalRegressionMixin, RegressionMixin):
>>>     ...

See RegressionMixin for more information.

The conditional model removes any random effects and models them as categorical fixed effects. These categorical effects are effect encoded.

Attributes

conditionalbool

Whether to fit a conditional model or not.

__init__(*args, conditional=False, **kwargs)

Initializes the mixin.

Parameters

conditionalbool

Whether to create a conditional model or not.

Methods

ConditionalRegressionMixin.formula([labels])	Creates the prediction formula of the fit for the encoded and normalized data.
ConditionalRegressionMixin.model_formula(model)	Creates the prediction formula of the fit for the encoded and normalized data.