Methods for Dimension Reduction for Regression
Description
Functions, methods, and datasets for fitting dimension
reduction regression, using slicing (methods SAVE and SIR), Principal
Hessian Directions (phd, using residuals and the response), and an
iterative IRE. Partial methods, that condition on categorical
predictors are also available. A variety of tests, and stepwise
deletion of predictors, is also included. Also included is
code for computing permutation tests of dimension. Adding additional
methods of estimating dimension is straightforward.
For documentation, see the vignette in the package. With version 3.0.4,
the arguments for dr.step have been modified.