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FRegSigCom (version 0.3.0)

pred.hd: Prediction for sparse linear function-on-function regression

Description

Make predition for functional response from the CV object obtained by cv.hd.

Usage

pred.hd(fit.cv, X.test, t.y.test=NULL)

Arguments

fit.cv

the CV object obtained by cv.hd.

X.test

new observations of functional predictors. It is a list of length \(p\), the number of functional predcitors. Each element is the observed matrix from a functional predictor, with rows repsenting observation vectors and columns corresponding to the observation time points.

t.y.test

a vector of observation time points where values of predicted response curves are to be calculated. If t.y.test=NULL (default), t.y in cv.hd will be used.

Value

A matrix containing the predicted values of response curves for the new observations. The number of rows equals to the sample size of the new data set, and the number of columns equals to the length of t.y.test or t.y when t.y.test=NULL.

See Also

cv.hd

Examples

Run this code
# NOT RUN {
 #See the examples in cv.hd().
# }

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