Dear Federico, The problem is the same with GLS residuals -- even if the GLS transformation produces homoskedastic errors, the residuals will be correlated and heteroskedastic (with this problem tending to disappear in most instances as n grows). The central point is that residuals don't behave quite the same as errors.
Regards, John -------------------------------- John Fox Department of Sociology McMaster University Hamilton, Ontario Canada L8S 4M4 905-525-9140x23604 http://socserv.mcmaster.ca/jfox -------------------------------- > -----Original Message----- > From: [EMAIL PROTECTED] > [mailto:[EMAIL PROTECTED] On Behalf Of > Federico Gherardini > Sent: Friday, October 15, 2004 11:22 AM > To: [EMAIL PROTECTED] > Subject: Re: [R] Testing for normality of residuals in a > regression model > > Thank you very much for your suggestions! The residuals come > from a gls model, because I had to correct for > heteroscedasticity using a weighted regression... can I > simply apply one of these tests (like shapiro.test) to the > standardized residuals from my gls model? > > Cheers, > Federico > > ______________________________________________ > [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 > ______________________________________________ [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