Thank you very much for the answer, it helped me a lot! Regards,
Sabine Woschitz -------- Original-Nachricht -------- > Datum: Sat, 12 Feb 2011 01:04:46 -0800 (PST) > Von: "Matthieu Lesnoff [via R]" > <ml-node+3302494-847497758-212...@n4.nabble.com> > An: sabwo <sab...@gmx.at> > Betreff: Re: Comparison of glm.nb and negbin from the package aod > > > Dear Sabine > > In negbin(aod), the deviance is calculated by: > > # full model > logL.max <- sum(dpois(x = y, lambda = y, log = TRUE)) > # fitted model > logL <- -res$value > dev <- -2 * (logL - logL.max) > > (the log-Lik contain all the constants) > > As Ben Bolker said, whatever the formula used for deviance, differences > between deviances of two models should be the same > > Regards > > -- > ------------------ > Matthieu Lesnoff > > On 10/02/2011 18:00, sabwo wrote: > > > > I have fitted the faults.data to glm.nb and to the function negbin from > the > > package aod. The output of both is the following: > > > > summary(glm.nb(n~ll, data=faults)) > > > > Call: > > glm.nb(formula = n ~ ll, data = faults, init.theta = 8.667407437, > > link = log) > > > > Deviance Residuals: > > Min 1Q Median 3Q Max > > -2.0470 -0.7815 -0.1723 0.4275 2.0896 > > > > Coefficients: > > Estimate Std. Error z value Pr(>|z|) > > (Intercept) -3.7951 1.4577 -2.603 0.00923 ** > > ll 0.9378 0.2280 4.114 3.89e-05 *** > > --- > > Signif. codes: 0 â***â 0.001 â**â 0.01 â*â 0.05 â.â 0.1 > â â 1 > > > > (Dispersion parameter for Negative Binomial(8.6674) family taken to be > 1) > > > > Null deviance: 50.28 on 31 degrees of freedom > > Residual deviance: 30.67 on 30 degrees of freedom > > AIC: 181.39 > > > > Number of Fisher Scoring iterations: 1 > > > > > > Theta: 8.67 > > Std. Err.: 4.17 > > > > 2 x log-likelihood: -175.387 > > > > the output of the function negbin with a global dispersion parameter > should > > - when i understood it right - yield the same estimates as glm.nb. it > does, > > with slightly little differences. > > > >> negbin(n~ll,~1, data=faults) > > Negative-binomial model > > ----------------------- > > negbin(formula = n ~ ll, random = ~1, data = faults) > > > > Convergence was obtained after 112 iterations. > > > > Fixed-effect coefficients: > > Estimate Std. Error z value Pr(> |z|) > > (Intercept) -3.795e+00 1.421e+00 -2.671e+00 7.570e-03 > > ll 9.378e-01 2.221e-01 4.222e+00 2.417e-05 > > > > Overdispersion coefficients: > > Estimate Std. Error z value Pr(> z) > > phi.(Intercept) 1.154e-01 5.56e-02 2.076e+00 1.895e-02 > > > > Log-likelihood statistics > > Log-lik nbpar df res. Deviance AIC AICc > > -8.77e+01 3 29 5.209e+01 1.814e+02 1.822e+02 > > > > The thing i really dont understand is why there is such a big difference > > between the deviances? (glm.nb = 30.67 and negbin=52.09?) Shouldnt they > be > > nearly the same?? > > > > thanks for your help, > > sabine > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > > > _______________________________________________ > If you reply to this email, your message will be added to the discussion > below: > http://r.789695.n4.nabble.com/Comparison-of-glm-nb-and-negbin-from-the-package-aod-tp3299679p3302494.html > > To unsubscribe from Comparison of glm.nb and negbin from the package aod, > visit > http://r.789695.n4.nabble.com/template/NamlServlet.jtp?macro=unsubscribe_by_code&node=3299679&code=c2Fic2l3QGdteC5hdHwzMjk5Njc5fC0yMjc1NTA5NTA= -- GMX DSL Doppel-Flat ab 19,99 Euro/mtl.! Jetzt mit gratis Handy-Flat! http://portal.gmx.net/de/go/dsl -- View this message in context: http://r.789695.n4.nabble.com/Comparison-of-glm-nb-and-negbin-from-the-package-aod-tp3299679p3308515.html Sent from the R help mailing list archive at Nabble.com. [[alternative HTML version deleted]]
______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
