[R] Loess fit
Liaw, Andy
andy_liaw at merck.com
Mon May 17 15:38:30 CEST 2010
I'm just guessing (since as David pointed out, no reproducible example
were given), but this perhaps could be the problem:
R> x <- 1:10
R> y <- rnorm(x)
R> fm <- loess(y ~ x)
R> predict(fm, data.frame(x=5:15))
[1] 0.1830450 0.2145826 -0.2158466 -0.3051978 -0.2635318 -0.1013985
[7] NA NA NA NA NA
Andy
From: David Winsemius
>
> On May 17, 2010, at 4:47 AM, Chintanu wrote:
>
> > Hi,
> >
> > I wonder why my attempt to extend an existing loess fit to
> a new data
> > set is producing error. I was trying the following:
> >
> > dat = read.csv(choose.files())
> > x = dat[,2]; y = dat[,1]
> > x.sort = sort(x)
>
> That is not needed, furthermore, you don't even use it.
>
> > y.loess = loess(y~x, span=0.75)
> >
> > # For testing the above fit with a new dataset:
> >
> > test = read.csv(choose.files()) # test data new_x = test
> [,1]; new_y =
> > test[,2] new_x.sort = sort(new_x)
>
> That sort is not needed.
>
> > predicted <- predict(y.loess, newdata=new_x.sort)
> >
> > Am I doing any mistake ? Please correct me.
>
> How can we tell when the inputs to these functions are not offered?
>
>
> >
> > I could see that though the rest of the values of "predicted" looks
> > alright, however the first output of it is an NA !!
>
> Perhaps outside the range of the loess function that was generated?
>
> dat = matrix(rnorm(100), ncol=2); x = dat[,2]; y = dat[,1]
> predicted <- predict(y.loess, newdata=x<-1:10 ) predicted
> # [1] 0.1022490 0.2574732 NA NA NA
> NA NA NA
> # [9] NA NA
>
>
> >
> > Many thanks,
> >
> > Chintanu
> --
>
> David Winsemius, MD
> West Hartford, CT
>
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