predict.slos {PFLR}

Predict Method for SLoS objects

Description

Predicted values based on objects of class "slos".

Usage

## S3 method for class 'slos'
predict(object, Xnew, ...)

Arguments

object

An object of class "slos".

Xnew

New covariate matrix for prediction, should be dense, centred.

...

Not applicable

Value

Predicted values.

Examples

library(fda)
betaind = 1
snr  = 2
nsim = 1
n    = 50
p    = 21
Y = array(NA,c(n,nsim))
X = array(NA,c(n,p,nsim))
domain = c(0,1)

M = 20
d = 3
norder   = d+1
nknots   = M+1
knots    = seq(domain[1],domain[2],length.out = nknots)
nbasis   = nknots + norder - 2
basis    = create.bspline.basis(knots,nbasis,norder)
V = eval.penalty(basis,int2Lfd(2))

extra=list(lambda=exp(seq(-18,-12, length.out = 10)),gamma=10^(-8:-6))

for(itersim in 1:nsim)
{
 dat = ngr.data.generator.bsplines(n=n,nknots=64,norder=4,p=p,domain=domain,snr=snr,betaind=betaind)
  Y[,itersim]  = dat$Y
  X[,,itersim] = dat$X
}

slosfit = SLoS(Y=Y[1:n,1],(X[1:n,,1]),M=M,d=d,domain=domain,extra=extra)

predict(slosfit,(X[1:n,,1]))