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Hm, I should have checked what would happen with binary data and not just continuous. Using glm with quasi(var="mu(1-mu)", link=logit) indeed fails with NAs/NaNs when y is binary. -- Hong Ooi Senior Research Analyst, IAG Limited 388 George St, Sydney NSW 2000 (02) 9292 1566 -----Original Message----- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Sundar Dorai-Raj Sent: Monday, 28 November 2005 11:20 PM To: Björn Stollenwerk Cc: [email protected] Subject: Re: [R] glm: quasi models with logit link function and binary data This is an issue with the starting values provided to glm. Take a look at the difference between: quasibinomial()$initialize and quasi("logit")$initialize and where this is used in glm.fit and you should see the why the error occurs. To avoid this, you can supply your own starting values from a call to glm mustart <- predict(glm(y ~ 1, binomial), type = "response") glm(y ~ 1, quasi("logit"), mustart = mustart) or just use: glm(y ~ 1, quasi("logit"), mustart = rep(0.5, length(y))) HTH, --sundar ______________________________________________ [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 _______________________________________________________________________________________ The information transmitted in this message and its attachme...{{dropped}} ______________________________________________ [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
