Looks ok to me, provided that you want averages (on log scale) taken over the the observed covariate values. If you want variances for the means you could always do something like the following...
Xa <- model.matrix(~as.factor(year)-1) Xa <- t(Xa)/colSums(Xa) ## Xa%*%fitted(g1) gives required averages Xp <- predict(g1,type="lpmatrix") ## Xp%*%coef(g1) gives fitted values Xm <- Xa%*%Xp ## now Xm%*%coef(g1) gives required averages yearly.means <- Xm%*%coef(g1) ym.cov <- Xm%*%vcov(g1,freq=FALSE)%*%t(Xm) ## cov matrix of yearly means (help file for predict.gam has a bit more information on this sort of thing, or section 5.2.6 of my book) best, Simon -- > Simon Wood, Mathematical Sciences, University of Bath, Bath, BA2 7AY UK > +44 1225 386603 www.maths.bath.ac.uk/~sw283 > > The covariates are year, month, vessel and statistical rectangle. > > > The model looks like this: > > g1 <- gam(log(cpue) ~ s(rekt1) + s(year) + s(mon) + s(reg1), data = > dataTest) > > > Once the model is fitted to the data I want to get the mean model > estimates by year. > > I do the following: > > obsPred <- data.frame(year = dataTest$year, pred = predict(g1, type = > "response")) > > gamFit <- tapply(obsPred$pred, list(year = obsPred$ar), mean) > > > > Is this correct? > > > > Thanks in advance > > > version > > _ > platform i386-pc-mingw32 > arch i386 > os mingw32 > system i386, mingw32 > status > major 2 > minor 4.1 > year 2006 > month 12 > day 18 > svn rev 40228 > language R > version.string R version 2.4.1 (2006-12-18) > > ______________________________________________ > R-help@stat.math.ethz.ch 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@stat.math.ethz.ch 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.
