ENV: Envelope Regression for Sufficient Dimension Reduction

In abnormally-distributed/cvreg: Cross Validation and Robust Estimation Utilities

Description

This is an adaptation with some improvements on functions in the Renvlp package. This can fit envelope models for dimension reduction to either univariate or multivariate numeric responses with numeric predictors. In the case of a univaraite outcome, a predictor envelope model is fit. For multivariate outcomes, an envelope is fit to both the response matrix and model matrix.

Usage

ENV(formula, data, rank = "all", yrank = "all", se = TRUE, init = NULL)

Arguments

formula	model formula
data	data frame
rank	number of dimensions
yrank	number of dimensions for a multivariate response.
se	should standard errors for the regression basis be calculated? defaults to TRUE.
init	an optional initial covariate dimension reduction subspace. defaults to NULL.

Value

an sdr object

abnormally-distributed/cvreg documentation built on May 3, 2020, 3:45 p.m.