DR: Directional Regression

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

Description

Directional regression (DR) is a second-order method somewhat similar to contour regression, but is simpler to compute and efficient than Contour Regression. While contour regression can be seen as a method for selecting empirical directions within the central subspace, DR is a method for reorganizing empirical directions (Li & Wang, 2007).

Usage

DR(
  formula,
  data,
  rank = "all",
  slices = 5,
  ytype = c("numeric", "categorical")
)

Arguments

formula	a model formula
data	a data frame
rank	the desired number of sufficient predictors to return. the default is "all".
slices	the number of slices into which the response variable should be split. defaults to 5. for categorical response variables the maximum allowed is the number of response levels minus one. if set above this, it is silently adjusted.
ytype	either numeric or categorical

References

Li, B.; Wang, S. (2007) On directional regression for dimension reduction. Journal of the American Statistical Association, 102, 997–1008

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