Hi Oliver, As a warning, I may be missing something too. I did not see something explicit in base R or MASS. In a quick scan of the fourth edition of the MASS book, I did not read anything that it is illogical/unreasonable to try to find standardized residuals (but my knowledge of local regression approaches nil). With that background, I proceeded to blithely scavenge from other functions until I came up with this:
loess.stdres <- function(model) { res <- model$residuals s <- sqrt(sum(res^2)/(length(res) - model$enp)) stdres <- res/(sqrt(1 - hat(res)) * s) return(stdres) } ## now for a half-baked check ## fit linear model and local regression cars.lm <- lm(dist ~ speed, cars) cars.lo <- loess(dist ~ speed, cars) ## these seem somewhat similar rstandard(cars.lm) c(scale(residuals(cars.lm))) ## these seem somewhat similar too loess.stdres(cars.lo) c(scale(cars.lo$residuals)) Cheers, Josh On Wed, Nov 10, 2010 at 9:24 AM, Oliver Frings <oliverfri...@googlemail.com> wrote: > Hi all, > > I'm trying to apply loess regression to my data and then use the fitted > model to get the *standardized/studentized residuals. I understood that for > linear regression (lm) there are functions to do that:* > * > * > fit1 = lm(y~x) > stdres.fit1 = rstandard(fit1) > studres.fit1 = rstudent(fit1) > > I was wondering if there is an equally simple way to get > the standardized/studentized residuals for a loess model? BTW > my apologies if there is something here that I'm missing. > > All the best, > * > * > *Oliver * > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > -- Joshua Wiley Ph.D. Student, Health Psychology University of California, Los Angeles http://www.joshuawiley.com/ ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.