View source: R/predict.fregre.fr.r
predict.fregre.fr | R Documentation |
Computes predictions for regression between functional explanatory variables and functional response.
## S3 method for class 'fregre.fr' predict(object, new.fdataobj = NULL, ...)
object |
|
new.fdataobj |
New functional explanatory data of |
... |
Further arguments passed to or from other methods. |
Return the predicted functional data.
Manuel Febrero-Bande, Manuel Oviedo de la Fuente manuel.oviedo@udc.es
See Also as: fregre.basis.fr
## Not run: # 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) } ## End(Not run)
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