Dear Kjetil, I don't believe that these are BLUS residuals, but since the last n - r "effects" are projections onto an orthogonal basis for the residual subspace, they should do just fine (as long as the basis vectors have the same length, which I think is the case, but perhaps someone can confirm). The general idea is to transform the LS residuals into an uncorrelated, equal-variance set.
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: Kjetil Brinchmann Halvorsen [mailto:[EMAIL PROTECTED] > Sent: Friday, October 15, 2004 9:12 AM > To: John Fox > Cc: 'Federico Gherardini'; [EMAIL PROTECTED] > Subject: Re: [R] Testing for normality of residuals in a > regression model > > John Fox wrote: > > >Dear Federico, > > > >A problem with applying a standard test of normality to LS > residuals is > >that the residuals are correlated and heterskedastic even if the > >standard assumptions of the model hold. In a large sample, this is > >unlikely to be problematic (unless there's an unusual data > >configuration), but in a small sample the effect could be nontrivial. > > > >One approach is to use BLUS residuals, which transform the > LS residuals > >to a smaller set of uncorrelated, homoskedastic residuals > (assuming the > >correctness of the model). > > > I'm not sure if this are BLUE residuals, but the following > function transform to a smaller set of independent, > homoscedastic residuals and the calls > shapiro.test: > I've proposed to make this a method for shapiro.test for "lm" > objects, but it is not accepted. > > shapiro.test.lm > function (obj) > { > eff <- effects(obj) > rank <- obj$rank > df.r <- obj$df.residual > if (df.r < 3) > stop("To few degrees of freedom for residual for the test.") > data.name <- deparse(substitute(obj)) > x <- eff[-(1:rank)] > res <- shapiro.test(x) > res$data.name <- data.name > res$method <- paste(res$method, " for residuals of linear model") > res > } > > Kjetil > > > > A search of R resources didn't turn up anything for BLUS, but they > >shouldn't be hard to compute. This is a standard topic > covered in many > >econometrics texts. > > > >You might consider the alternative of generating a bootstrapped > >confidence envelope for the QQ plot; the qq.plot() function > in the car > >package will do this for a linear model. > > > >I hope this helps, > > 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 7:44 AM > >>To: [EMAIL PROTECTED] > >>Subject: [R] Testing for normality of residuals in a > regression model > >> > >>Hi all, > >> > >>Is it possible to have a test value for assessing the normality of > >>residuals from a linear regression model, instead of simply > relying on > >>qqplots? > >>I've tried to use fitdistr to try and fit the residuals > with a normal > >>distribution, but fitdsitr only returns the parameters of the > >>distribution and the standard errors, not the p-value. Am I missing > >>something? > >> > >>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 > > > > > > > > > > > -- > > Kjetil Halvorsen. > > Peace is the most effective weapon of mass construction. > -- Mahdi Elmandjra > > > ______________________________________________ [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