asmbPLS.predict {asmbPLS}

Using an asmbPLS model for prediction of new samples

Description

Derives predictions for new samples from a model fitted by the function asmbPLS.fit or mbPLS.fit.

Usage

asmbPLS.predict(fit.results, X.matrix.new, PLS.comp)

Arguments

fit.results

The output of either asmbPLS.fit or mbPLS.fit.

X.matrix.new

A predictors matrix, whose predictors are the same as the predictors in model fitting.

PLS.comp

Number of PLS components used for prediction.

Value

asmbPLSDA.predict returns a list containing the following components:

Y_pred

Predicted value for the new sampels.

NewX_super_score

Predicted super score for new samples, which can be used as predictors for other regression models.

Examples

## Use the example dataset
data(asmbPLS.example)
X.matrix = asmbPLS.example$X.matrix
X.matrix.new = asmbPLS.example$X.matrix.new
Y.matrix = asmbPLS.example$Y.matrix
PLS.comp = asmbPLS.example$PLS.comp
X.dim = asmbPLS.example$X.dim
quantile.comb = asmbPLS.example$quantile.comb
 
## asmbPLS fit
asmbPLS.results <- asmbPLS.fit(X.matrix = X.matrix, 
                               Y.matrix = Y.matrix, 
                               PLS.comp = PLS.comp, 
                               X.dim = X.dim, 
                               quantile.comb = quantile.comb)

## asmbPLS prediction for the new data, you could use different numbers of 
## PLS components for prediction
## Use only the first PLS component 
Y.pred.1 <- asmbPLS.predict(asmbPLS.results, X.matrix.new, 1)
## Use the first two PLS components
Y.pred.2 <- asmbPLS.predict(asmbPLS.results, X.matrix.new, 2)