dr (version 1.0.2)

dr.directions: Directions selected by dimension reduction regressiosn

Description

Dimension reduction regression returns a set of p orthogonal direction vectors each of length p, the first d of which are estimates a basis of a d dimensional central subspace. The function returns the estimated directions in the original n dimensional space for plotting.

Usage

dr.direction(object, which, norm, x)
dr.directions(object, which, norm, x)
dr.direction.default(object, which=1:object$numdir,norm=F,x=dr.x(object))

Arguments

object

a dimension reduction regression object

which

select the directions wanted, default is all directions

norm

if TRUE, direction vectors are normalized to length 1, otherwise their length is arbitrary

x

select the X matrix, the default is dr.x(object)

...

additional arguments are passed to dr.direction.default

Value

• Returns a matrix. The same function has two names.

Details

Dimension reduction regression is used to estimate a basis of the central subspace of a regression. If there are p predictors, the dimension reduction regression object includes a p by p matrix of C of eigenvectors. This method returns (X-m1')C where m is the vector of column means of X. If X is equal to the original matrix of predictors given by dr.x(object), then this gives the directions in the coordinates of the orginal n dimensional space. These directions are used in graphical methods and elsewhere.

References

See R. D. Cook (1998). Regression Graphics. New York: Wiley.

See Also

dr

Examples

library(dr)
data(ais)
attach(ais)  # the Australian athletes data
#fit dimension reduction using sir
m1 <- dr(LBM~Wt+Ht+RCC+WCC, method="sir", nslices = 8)
summary(m1)
dr.directions(m1)