Thanks a lot Bert. Yet still, I would like to know does the diagnosis and model-checking for rlm follow the same procedure as lm ...
Thank you! On Fri, Jul 6, 2012 at 9:27 AM, Bert Gunter <[email protected]> wrote: > .... > > On Fri, Jul 6, 2012 at 7:19 AM, Michael <[email protected]> wrote: > >> Hi all, >> >> I am reading the MASS book but it doesn't give examples about the >> diagnosis >> and model checking for rlm... >> >> My data is highly non-Gaussian so I am using rlm instead of lm. >> > > Well, rlm() is not necessarily going to help you with that. Key questions: > In what way are the data non-Gaussian? Why? > > Please do not reply to either me or the list. You need to talk with a > statistician or try a statistical help list (e.g. stats.stackexchange.com). > These are not questions about R but about statistical modeling. > > -- Bert > >> >> My questions are: >> >> 0. Are goodness-of-fit and model-checking using rlm completely the same as >> usual regression? >> >> 1. >> >> >> Please give me some pointers about how to do goodness-of-fit and >> residual diagnosis for rlm in R? Any good tutorials/examples, etc? >> 2. >> >> >> How to do the residual diagnosis etc. when regression weights are used? >> Still the same? >> >> Thanks a lot! >> >> [[alternative HTML version deleted]] >> >> ______________________________________________ >> [email protected] mailing list >> https://stat.ethz.ch/mailman/listinfo/r-help >> PLEASE do read the posting guide >> http://www.R-project.org/posting-guide.html<http://www.r-project.org/posting-guide.html> >> and provide commented, minimal, self-contained, reproducible code. >> > > > > -- > > Bert Gunter > Genentech Nonclinical Biostatistics > > Internal Contact Info: > Phone: 467-7374 > Website: > > http://pharmadevelopment.roche.com/index/pdb/pdb-functional-groups/pdb-biostatistics/pdb-ncb-home.htm > > > [[alternative HTML version deleted]] ______________________________________________ [email protected] 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.
