predict.mvr: Predict Method for PLSR and PCR

Description

Prediction for MVR (PCR, PLSR) models. New responses or scores are predicted using a fitted model and a new matrix of observations.

Usage

## S3 method for class 'mvr':
predict(object, newdata, comps = 1:object$ncomp,
        type = c("response", "scores"), cumulative = TRUE, ...)

Arguments

Value

When type is "response", a three dimensional array of predicted response values is returned. The dimensions correspond to the observations, the response variables and the model sizes, respectively.
When type is "scores", a score matrix is returned.

Details

When type is "response" (default), predicted response values are returned. If cumulative is TRUE, the elements of comps are interpreted cumulatively, i.e. predictions for models with comps[1] components, comps[2] components, etc., are returned. Otherwise, predicted response values for a single model with the exact components in comps are returned.

When type is "scores", predicted score values are returned for the components given in comps.

Examples

Run this code

data(NIR)
nir.mvr <- mvr(y ~ X, ncomp = 5, data = NIR[NIR$train,])

## Predicted responses for models with 1, 2, 3 and 4 components
pred.resp <- predict(nir.mvr, comps = 1:4, newdata = NIR[!NIR$train,])

## Predicted responses for a single model with components 1, 2, 3, 4
predict(nir.mvr, comps = 1:4, cumulative = FALSE, newdata = NIR[!NIR$train,])

## Predicted scores
predict(nir.mvr, comps = 1:3, type = "scores", newdata = NIR[!NIR$train,])

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