OlsModel

class pyoptex.analysis.estimators.sams.models.ols_model.OlsModel(*args, **kwargs)

A default OLS model for use with the SAMS algorithm which extends the Model interface.

Attributes

Xnp.array(2d)

The encoded, normalized model matrix of the data

ynp.array(1d)

The output variable.

forcednp.array(1d)

Any terms that must be included in the model.

modeNone or ‘weak’ or ‘strong’

The heredity model during sampling.

depnp.array(2d)

The dependency matrix of size (N, N) with N the number of terms in the encoded model (output from Y2X). Term i depends on term j if dep(i, j) = true.

ss_interceptfloat

The sum of squared residuals for a model with only the intercept.

__init__(*args, **kwargs)

Initializes the OLS model

Parameters

Xnp.array(2d)

The encoded, normalized model matrix of the data.

ynp.array(1d)

The output variable.

forcednp.array(1d)

Any terms that must be included in the model.

modeNone or ‘weak’ or ‘strong’

The heredity model during sampling.

depnp.array(2d)

The dependency matrix of size (N, N) with N the number of terms in the encoded model (output from Y2X). Term i depends on term j if dep(i, j) = true.

Methods

OlsModel.fit(model)	Fits an OLS model
OlsModel.init(model)	Create a random model by sequential sampling.
OlsModel.mutate(model)	Mutate the model by removing atleast one term and replacing it.