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Loess fit
3 messages · Chintanu, David Winsemius, Liaw, Andy
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
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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