[R] Testing for normality of residuals in a regression model

[John Fox]

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: r-help-bounces at stat.math.ethz.ch 
> [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of 
> Federico Gherardini
> Sent: Friday, October 15, 2004 11:22 AM
> To: R-help at stat.math.ethz.ch
> 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
> 
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