statsmodels.regression.dimred.SlicedInverseReg

class statsmodels.regression.dimred.SlicedInverseReg(endog, exog, **kwargs)

Sliced Inverse Regression (SIR)

Parameters

endogarray_like (1d)

The dependent variable

exogarray_like (2d)

The covariates

References

KC Li (1991). Sliced inverse regression for dimension reduction. JASA 86, 316-342.

Attributes

endog_names

Names of endogenous variables.

exog_names

Names of exogenous variables.

Methods

fit([slice_n])	Estimate the EDR space using Sliced Inverse Regression.
fit_regularized([ndim, pen_mat, slice_n, …])	Estimate the EDR space using regularized SIR.
from_formula(formula, data[, subset, drop_cols])	Create a Model from a formula and dataframe.
predict(params[, exog])	After a model has been fit predict returns the fitted values.

Methods

fit([slice_n])	Estimate the EDR space using Sliced Inverse Regression.
fit_regularized([ndim, pen_mat, slice_n, …])	Estimate the EDR space using regularized SIR.
from_formula(formula, data[, subset, drop_cols])	Create a Model from a formula and dataframe.
predict(params[, exog])	After a model has been fit predict returns the fitted values.

Properties

endog_names	Names of endogenous variables.
exog_names	Names of exogenous variables.