Predict.matrix.pcre.random.effect

a smooth specification object, see <code><a href="/link/smooth.construct?package=refund&version=0.1-1&to=mgcv" rd-options="mgcv" data-mini-rdoc="mgcv::smooth.construct">smooth.construct</a></code>

object

see <code><a href="/link/smooth.construct?package=refund&version=0.1-1&to=mgcv" rd-options="mgcv" data-mini-rdoc="mgcv::smooth.construct">smooth.construct</a></code>

data

mgcv-style constructor for prediction of PC-basis functional random effects

Functions for regression with functional data.  The
        principal methods currently implemented are (1)
        functional-response/scalar-predictor regression by penalized
        OLS or GLS; and (2) functional principal component regression
        for scalar responses and functional predictors.

Predict.matrix.pcre.random.effect: mgcv-style constructor for prediction of PC-basis functional random effects

Description

Usage

Arguments

Value