Jean, The standard treatment of overdispersed data when using the Poisson distribution to model count data is to switch to the negative binomial distribution. Hope this helps,
Tim Liao ---- Original message ---- >Date: Thu, 13 Jan 2005 18:22:29 -0500 >From: "Jean G. Orelien" <[EMAIL PROTECTED]> >Subject: [R] GAM: Remedial measures >To: <[email protected]> > >I fitted a GAM model with Poisson distribution to a data with about 200 >observations. I noticed that the plot of the residuals versus fitted values >show a trend. Residuals tend to be lower for higher fitted values. Because, >I'm dealing with count data, I'm thinking that this might be due to >overdispersion. Is there a way to account for overdispersion in any of the >packages MGCV or GAM? > > > >I welcome any suggestions that one may have on this topic. > > > >Jean > > > >________________ >______________________________________________ >[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
