Predict method for functional response model

Computes predictions for regression between functional explanatory variables and functional response.

Usage

# S3 method for class 'fregre.fr'
predict(object, new.fdataobj = NULL, ...)

Arguments

object

fregre.fr object.

new.fdataobj

New functional explanatory data of fdata class.

...

Further arguments passed to or from other methods.

Value

Return the predicted functional data.

See also

See Also as: fregre.basis.fr

Author

Manuel Febrero-Bande, Manuel Oviedo de la Fuente manuel.oviedo@udc.es

Examples

if (FALSE) { # \dontrun{ 
# CV prediction for CandianWeather data
rtt<-c(0, 365)
basiss  <- create.bspline.basis(rtt,7)
basist  <- create.bspline.basis(rtt,9)
nam<-dimnames(CanadianWeather$dailyAv)[[2]]

# fdata class (raw data)
tt<-1:365
tempfdata<-fdata(t(CanadianWeather$dailyAv[,,1]),tt,rtt)
log10precfdata<-fdata(t(CanadianWeather$dailyAv[,,3]),tt,rtt)
rng<-range(log10precfdata) 
for (ind in 1:35){
 res1<-  fregre.basis.fr(tempfdata[-ind], log10precfdata[-ind],
 basis.s=basiss,basis.t=basist)
 pred1<-predict(res1,tempfdata[ind])
 plot( log10precfdata[ind],col=1,ylim=rng,main=nam[ind])
 lines(pred1,lty=2,col=2)
 Sys.sleep(1)
}

# fd class  (smooth data)
basis.alpha  <- create.constant.basis(rtt)
basisx  <- create.bspline.basis(rtt,65)

dayfd<-Data2fd(day.5,CanadianWeather$dailyAv,basisx)
tempfd<-dayfd[,1]
log10precfd<-dayfd[,3]
for (ind in 1:35){
 res2 <-  fregre.basis.fr(tempfd[-ind], log10precfd[-ind],
 basis.s=basiss,basis.t=basist)
 pred2<-predict(res2,tempfd[ind])
 plot(log10precfd[ind],col=1,ylim=range(log10precfd$coef),main=nam[ind]) 
 lines(pred2,lty=2,col=2)
 Sys.sleep(.5)
}
} # }