Dear Alan, You can use the (generic) cooks.distance function in R, which uses the weighted residuals. See ?cooks.distance, and stats:::cooks.distance.lm for the function definition (i.e., the method for a linear model).
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 > Dorfman, Alan - BLS > Sent: Friday, February 11, 2005 11:08 AM > To: '[email protected]' > Subject: [R] cook's distance in weighted regression > > > I have a puzzle as to how R is computing Cook's distance in > weighted linear regression. > > In > this case cook's distance should be given not as in OLS case by > > h_ii*r_i^2/(1-hii)^2 divided by k*s^2 > (1) > (where r is plain unadjusted residual, k is number of > parameters in model, etc. ) > > but rather by > > w_ii*h_ii*r_i^2/(1-hii)^2 divided by k*s^2, > (2) > > i.e. has the weight in there. Apart from the division this is > sum of weighted squares of differences > > yhat_j - yhat_j[i]. (That is, it is the weighted sum of > squares of fits minus fits with ith point deleted.) > > However, a little experimentation in R, using > ls.diag(fit)$cooks, suggests that in weighted case R gives > (1) times some constant. Does anybody know how that constant > is calculated? What is the rationale for using equation (1) > (times a constant) in the weighted case anyway? > Thanks. > > > > > [[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 ______________________________________________ [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
