predictValuesLm {rotRPackage}R Documentation

Predicts values through a linear model

Description

This ROT function, called from a LinearModel C++ object, and given a sample, is used to predict the corresponding values through the linear model. It returns the predicted sample.

Usage

predictValuesLm(x, beta)

Arguments

x A m-by-n matrix containing the explanatory variables.
beta A n-by-1 vector containng the linear model parameters.

Details

As it is not asked in LinearModel.getPredict(), no prediction interval is returned; it is up to the user to be careful about that. It is also to noted that the sample is not assumed to contain the '1's corresponding to the intercept parameter.

Value

A m-by-1 vector is returned, containing the predicted values.

Author(s)

Pierre-Matthieu Pair, Softia for EDF.

Examples

set.seed(1)
x <- matrix(runif(40), 10, 4)
r <- matrix(c(1,2,3,4), 4, 1)
y <- x %*% r + matrix(rnorm(10, 0, 0.05), 10, 1)
LM <- computeLinearModel(x, y)
predictValuesLm(x, LM$parameterEstimate) 

[Package rotRPackage version 1.4.3 Index]