Dear Matias
predict.lmrob() seems not to exist and predict.lm() gives an incorrect result. Is there another convenient trick to predict other data than the fitted? Below you 'll find a short example.
library(robustbase)
xy <- data.frame(x=1:10, y=(1:10)+rnorm(10))
res <- lmrob(y~x, xy)
fitted(res)
## correct
predict(res,newdata=data.frame(x=10:20))
## Error in predict(res, newdata = data.frame(x = 10:20)) :
## no applicable method for "predict"
predict.lm(res,newdata=data.frame(x=10:20))
## does not work properly!
sessionInfo()
## R version 2.5.1 (2007-06-27)
## i386-pc-mingw32
##
## locale:
## LC_COLLATE=German_Switzerland.1252;LC_CTYPE=German_Switzerland.1252;LC_MONETARY=German_Switzerland.1252;LC_NUMERIC=C;LC_TIME=German_Switzerland.1252
##
## attached base packages:
## [1] "stats" "graphics" "grDevices" "utils" "datasets" "methods"
## [7] "base"
##
## other attached packages:
## robustbase
## "0.2-8"
Kind regards and thanks in advance
Ren?
Ren? Locher E-Mail: rene.locher at zhaw.ch
Institut f?r Datenanalyse und Prozessdesign Tel: +41 58 934 7810
Z?rcher Hochschule f?r angewandte Wissenschaften Fax: +41 58 935 7810
Rosenstrasse 3
Postfach
CH-8400 Winterthur http://www.idp.zhaw.ch