From: christophe dutang <dutangc_at_gmail.com>

Date: Thu, 28 Aug 2008 09:58:34 +0200

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https://stat.ethz.ch/mailman/listinfo/r-devel Received on Thu 28 Aug 2008 - 17:23:01 GMT

Date: Thu, 28 Aug 2008 09:58:34 +0200

Hi,

Thanks for answering so quickly.

Actually, I do not have the John Fox's book. On this webpage, there is a handout for logistic regression (GLM I'm interested in) (cf. http://socserv.socsci.mcmaster.ca/jfox/Courses/SPIDA/logistic-regression-handout.pdf).

The summary function return standard errors for coefficient estimates but
not for predictions. According to

http://www.nag.co.uk/numeric/cl/Manual/pdf/G02/g02gbc.pdf<http://www.nag.co.uk/numeric/cl/Manual/pdf/G02/g02gbc.pdfprovides>
the standard errors for the linear predictors X \hat{\beta} is X C X^t where
C is the variance/covariance matrix of coefficient estimate \hat{\beta} .
But I do not know standard errors for a response.

Christophe

2008/8/27 <markleeds_at_verizon.net>

*> Hi: you can check John Fox's CAR book if you have it. I don't remember for
**> sure but I may have standard error related calculations for some of
**> his graphics in the GLM section of the book ? But, Can you not get the
**> sigma^2 hat the summary of a GLM ? i would do
**>
**> glmsum<-summary("yourglmmodel") and check there.
**>
**> I'd be really surprised if the variance of the error term wasn't there.
**> Then, if you have that I think you can use that to calculate the prediction
**> standard error as long as you assume that the parameters of the model are
**> known with certainty. The formula for that is in the regular regression (
**> non GLM ) textbooks but i don't remember it off the top of my head. Good
**> luck and hopefully someone else will reply with more exact info.
**>
**>
**>
**>
**>
**>
**> On Wed, Aug 27, 2008 at 1:25 PM, christophe dutang wrote:
**>
**> Hi,
**>>
*

>> I'm currently using biglm package to compute GLM outputs on a very large

*>> dataset. But no function computes standard erros of predictions. I look in
**>> what is done in R, namely in the function predict.glm.R in stats package.
**>> In this function, we call predict.lm to compute the standard errors (line
**>> 51). The code of predict.lm (in lm.R) is very hard to understand.
**>>
**>> I wonder if there is any good reference and / documentation on this topic?
**>> the manual at
**>> http://www.nag.co.uk/numeric/cl/Manual/pdf/G02/g02gbc.pdfprovides
**>> a good overview of the method used in R, but there is no reference
**>> to standard errors...
**>>
**>> I suppose this topic have already raised in the past, but I found only
**>> this
**>> http://tolstoy.newcastle.edu.au/R/help/04/08/1762.html
**>>
**>> Thanks in advance
**>>
**>> Christophe
**>>
**>> [[alternative HTML version deleted]]
**>>
**>> ______________________________________________
**>> R-devel_at_r-project.org mailing list
**>> https://stat.ethz.ch/mailman/listinfo/r-devel
**>>
**>
*

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