statsmodels.regression.dimred.PrincipalHessianDirections

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

Principal Hessian Directions (PHD)

Parameters:

endog : array_like (1d)

The dependent variable

exog : array_like (2d)

The covariates

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.

Attributes

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

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.

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.