statsmodels.regression.dimred.SlicedInverseReg

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

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.