predict.penv: Estimation or prediction for penv

In therimalaya/envelope: Computing Envelope Estimators in Multivariate Linear Regression

Description

Perform estimation or prediction under the partial envelope model.

Usage

predict.penv(m, X1new, X2new)

Arguments

m	A list containing estimators and other statistics inherited from penv.
X1new	The value of X1 with which to estimate or predict Y. A p1 dimensional vector.
X2new	The value of X2 with which to estimate or predict Y. A p2 dimensional vector.

Details

This function evaluates the partial envelope model at new value Xnew. It can perform estimation: find the fitted value when X = Xnew, or prediction: predict Y when X = Xnew. The covariance matrix and the standard errors are also provided.

Value

The output is a list that contains following components.

value	The fitted value or the predicted value evaluated at X1new and X2new.
covMatrix.estm	The covariance matrix of the fitted value at X1new and X2new.
SE.estm	The standard error of the fitted value at X1new and X2new.
covMatrix.pred	The covariance matrix of the predicted value at X1new and X2new.
SE.pred	The standard error of the predicted value at X1new and X2new.

Examples

data(fiberpaper)
X1 <- fiberpaper[, 7]
X2 <- fiberpaper[, 5:6]
Y <- fiberpaper[, 1:4]
m <- penv(X1, X2, Y, 2)

pred.res <- predict.penv(m, X1[1], X2[1, ])
pred.res

therimalaya/envelope documentation built on May 29, 2019, 1:38 p.m.