[R] Variance-covariance matrix from GLM

Hello, Is there a way to obtain the variance-covariance matrix of the estimated parameters from GLM? my.glm-glm(mat ~X,family = binomial, data =myDATA) out1-predict(my.glm,se.fit = TRUE) std-out1$se.fit se.fit is for getting the standard errors of the estimated parameters (\betas). Is there

Re: [R] Variance-covariance matrix from GLM

?vcov ### now in the stats package You would use V - vcov(my.glm) -Original Message- From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On Behalf Of Bojuan Zhao Sent: Thursday, 29 July 2010 9:52 AM To: r-help@r-project.org Subject: [R] Variance-covariance

Re: [R] Variance-covariance matrix from GLM

Fantastic! it's solved! Thank you very much Bill! Barbara --- On Wed, 7/28/10, bill.venab...@csiro.au bill.venab...@csiro.au wrote: From: bill.venab...@csiro.au bill.venab...@csiro.au Subject: RE: [R] Variance-covariance matrix from GLM To: bojuanz...@yahoo.com, r-help@r-project.org Date

[R] variance covariance matrix in GLM

this is for the person who asked me about prediction confidence intervals in a GLM because I lost your email. Below follows a simple example in CAR and the variance covariance of the beta coefficients is in the summary. So, I think, given that output, it should be pretty straightforward to do