statsmodels.regression.dimred.PrincipalHessianDirections

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

Principal Hessian Directions (PHD)

Parameters:
endogarray_like (1d)

The dependent variable

exogarray_like (2d)

The covariates

Attributes:
endog_names

Names of endogenous variables.

exog_names

Names of exogenous variables.

Returns:
A model instance. Call fit to obtain a results instance,
from which the estimated parameters can be obtained.

References

KC Li (1992). On Principal Hessian Directions for Data Visualization and Dimension Reduction: Another application of Stein’s lemma. JASA 87:420.

Methods

fit(**kwargs)

Estimate the EDR space using PHD.

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.


Last update: Oct 03, 2024