Methods for Dimension Reduction for Regression
Swiss banknote data
Internal function to find the basis of a subspace
Dimension reduction tests
Directions selected by dimension reduction regressiosn
Permutation tests of dimension for dr
Compute the Chi-square approximations to a weighted sum of Chi-square(...
Main function for dimension reduction regression
Divide a vector into slices of approximately equal size
Estimate weights for elliptical symmetry
Accessor functions for data in dr objects
Sequential fitting of coordinate tests using a dr object
Basic plot of a dr object
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.