pred.SiER: Prediction for high-dimensional multivariate regression

In SiER: Signal Extraction Approach for Sparse Multivariate Response Regression

Description

Make prediction for the univariate or multivariate response based on new observations of predictors from the CV object obtained by cv.SiER.

Usage

pred.SiER(cv.fit, X.new)

Arguments

cv.fit	the CV object obtained by cv.SiER().
X.new	a new data matrix for predictors. The number of columns equals to the number of variables.

Value

A matrix containing the predicted response for new observations. The number of rows is equal to the number of observations in the new data set, and the number of columns is equal to the number of the responses.

Author(s)

Ruiyan Luo and Xin Qi

See Also

cv.SiER

Examples

#See the examples in cv.SiER().

SiER documentation built on May 2, 2019, 5:07 a.m.