Hi, If i understand what you mean, you can do Plot(M.gam.auto) You Will get the centered predictions for smooths, you can also extract predictions for each term using (predict(M.gam.auto, type="terms")).
The results you got are thé coefficients for each of you smooths pieces (as k=4, you get 3), but they re not interpretable as they are. Hope this could help Youssef Le 2012-09-05 à 11:50, fmoreira <fmore...@isa.utl.pt> a écrit : > Hi, > > It is not clear to me what a model-averaged (sensu MuMIn package) GAM is... > How is the smoother averaged and how can I see it ? > > My model is: > > M.gam.auto <- gam (Leksite ~ s(Altmean,k=4) + s(Class_unfav_prop, k=4) + > + s(Visib2000, k=4) + s(Ddisturbance, k=4) + s(Steppe_prop, > k=4) > + s(autocov2, k=4), family=binomial, data= leks) > > When i extract the confidence intervals for the average models (all models > with delta AIC <2), I get: > >> confint (avgmod) > 2.5 % 97.5 % > (Intercept) -0.705495919 0.090974395 > s(Altmean).1 -1.032000478 0.846255206 > s(Altmean).2 -0.131526964 3.181165030 > s(Altmean).3 -0.479038766 1.511470593 > s(autocov2).1 -0.594732400 5.030680753 > s(autocov2).2 -3.932830030 18.377288299 > s(autocov2).3 -5.859925892 3.269061133 > s(Ddisturbance).1 -0.324700903 0.609412974 > s(Ddisturbance).2 -0.016172651 5.880936668 > s(Ddisturbance).3 -0.881357264 0.862160976 > s(Steppe_prop).1 -0.002864215 0.002861629 > s(Steppe_prop).2 -0.022374707 0.022389396 > s(Steppe_prop).3 0.191842041 1.242861265 > s(Class_unfav_prop).1 -0.119628517 0.109562147 > s(Class_unfav_prop).2 -0.246237564 0.274136388 > s(Class_unfav_prop).3 -0.588583036 0.189353845 > s(Visib2000).1 -0.003592773 0.003593891 > s(Visib2000).2 -0.012680896 0.012686619 > s(Visib2000).3 -0.489773942 0.206553913 > > Not sure of this means nor how to visualize the smoothers... > Help would be appreciated. > > > Francisco Moreira > Institute of Agronomy > Technical University of Lisbon > > > > -- > View this message in context: > http://r.789695.n4.nabble.com/how-to-visualise-the-smoothers-of-a-model-averaged-GAM-tp4642302.html > Sent from the R help mailing list archive at Nabble.com. > > ______________________________________________ > 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. ______________________________________________ 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.
