lmap (version 0.2.4)

predict.lpca: The function predict.lpca makes predictions for a test/validation set based on a fitted lrrr model (lpca with X)

Description

The function predict.lpca makes predictions for a test/validation set based on a fitted lrrr model (lpca with X)

Usage

# S3 method for lpca
predict(object, newX, newY = NULL, ...)

Value

This function returns an object of the class lpca with components:

theta

Predicted canonical values for the test set

Yhat

Predicted values for the test set

devr

Estimated prediction deviance for separate responses

devtot

Estimated prediction deviance for all responses

Brier.r

Estimated Brier score for separate responses

Brier

Estimated Brier score for all responses

Arguments

object

An lpca object

newX

An N by P matrix with predictor variables for a test/validation set

newY

An N by R matrix with response variables for a test/validation set

...

additional arguments to be passed.

Examples

if (FALSE) {
data(dataExample_lpca)
Y = as.matrix(dataExample_lpca[-c(1:20) , 1:8])
X = as.matrix(dataExample_lpca[-c(1:20) , 9:13])
newY = as.matrix(dataExample_lpca[1:20 , 1:8])
newX = as.matrix(dataExample_lpca[1:20 , 9:13])
# supervised
output = lpca(Y = Y, X = X, S = 2)
preds = predict(output, newX = newX, newY = newY)
}