gsave: gsave

In nsdr: Nonlinear Sufficient Dimension Reduction

Description

gsave

Usage

gsave(x,x.new,y,ytype,ex,ey,comx,comy,r)

Arguments

x	input predictor matrix from training set
x.new	input predictor matrix from testing set
y	response variables
ytype	type of response variables
ex	tuning parameter for the Tychonoff reguralized inverse for GX
ey	tuning parameter for the Tychonoff reguralized inverse for GY
comx	tuning parameter for the Gaussian kernel in X
comy	tuning parameter for the Gaussian kernel in Y
r	number of dimension

Value

pred: sufficient predictors from GSAVE

obj.mat: objective matrix of GSAVE

eig.val: the first r eigenvalues from the eigendecomposition of the objective matrix

eig.vec: the first r eigenvectors from the eigendecomposition of the objective matrix

References

Li, B. (2018). Sufficient dimension reduction: Methods and applications with R. CRC Press.

Examples

n = 50; p = 5; sigma = 1;
x = matrix(rnorm(n*p),n,p) ; err = rnorm(n)
y = x[,1]/(0.5+(x[,1]+1)^2) + sigma*err; ex=0.01 ; ey=0.01
gsave_res <- gsave(x,x,y,"scalar",ex,ey,1,1,1)

nsdr documentation built on June 3, 2021, 9:06 a.m.