Hello, I would like to know if there is any package that allow us to fit Generalized Linear Models via Maximum Likelihood and Linear Models using Generalized Least Squarse in R as the functions glim and gls, respectively, from S-Plus. Also, anybody know if there is any package that fit Log-Linear Models using Generalized Least Squares? Any help will be very useful. Thanks, -- Frederico Zanqueta Poleto fred at poleto.com - ICQ# 4129787 -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-help-request at stat.math.ethz.ch _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._
Douglas, First, I would like to thank your answear.>> I would like to know if there is any package that allow us to fit >> Generalized Linear Models via Maximum Likelihood and Linear Models using >> Generalized Least Squarse in R as the functions glim and gls, >> respectively, from S-Plus.> The glm function for generalized linear models is available in the > base package of R. That is, you can use it any time you start R. The > gls function for generalized least squares fits is available in the > nlme package for R.The glm function fits GLM using Iterative Reweighted Least Squares (IRLS) and I need to do it via Maximum Likelihood. Yes, I looked the package nlme and it has the function gls. Thanks.>> Also, anybody know if there is any package that fit Log-Linear Models >> using Generalized Least Squares?> There is a package GLMMGibbs for fitting generalized linear mixed > models. I'm not sure if that is what you want.No, GLMMGibbs fit GLMM via Gibbs Sampling, and again I need to do it via Geeralized Least Squares. I could also use the function loglin, but it uses Iterative Proportional Fitting. Best regards, -- Frederico Zanqueta Poleto fred at poleto.com -- "It would be possible to describe everything scientifically, but it would make no sense; it would be without meaning, as if you described a Beethoven symphony as a variation of wave pressure." Albert Einstein -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-help-request at stat.math.ethz.ch _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._
On 26 Oct 2001, Frederico Zanqueta Poleto wrote:> > Douglas, > > First, I would like to thank your answear. > > >> I would like to know if there is any package that allow us to fit > >> Generalized Linear Models via Maximum Likelihood and Linear Models using > >> Generalized Least Squarse in R as the functions glim and gls, > >> respectively, from S-Plus. > > > The glm function for generalized linear models is available in the > > base package of R. That is, you can use it any time you start R. The > > gls function for generalized least squares fits is available in the > > nlme package for R. > > The glm function fits GLM using Iterative Reweighted Least Squares (IRLS) > and I need to do it via Maximum Likelihood.IRLS *is* maximum likelihood for generalized linear models. -thomas Thomas Lumley Asst. Professor, Biostatistics tlumley at u.washington.edu University of Washington, Seattle -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-help-request at stat.math.ethz.ch _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._