statsmodels.regression.dimred.SlicedAverageVarianceEstimation

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

Sliced Average Variance Estimation (SAVE)

Parameters
endogarray_like (1d)

The dependent variable

exogarray_like (2d)

The covariates

bcbool, optional

If True, use the bias-corrected CSAVE method of Li and Zhu.

References

RD Cook. SAVE: A method for dimension reduction and graphics in regression. http://www.stat.umn.edu/RegGraph/RecentDev/save.pdf

Y Li, L-X Zhu (2007). Asymptotics for sliced average variance estimation. The Annals of Statistics. https://arxiv.org/pdf/0708.0462.pdf

Attributes
endog_names

Names of endogenous variables.

exog_names

Names of exogenous variables.

Methods

fit(**kwargs)

Estimate the EDR space.

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(**kwargs)

Estimate the EDR space.

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.