Hi R users, I'm using the 'bam' function in mgcv to examine trends in a remotely sensed vegetation index. I have one random effect variable, 'cons' (with six levels) which identifies different subjects within this analysis.
My model is specified as follows: rm4<-bam(trend~factor(zone)+s(cons,bs="re")+s(year, bs="cc"),data=rain.data,family=gaussian(link="identity"),method="ML",na.action=na.omit, rho=0.884) I'm using the bam routine as the dataframe is very large (>300,000 rows of data). If possible, I'd like to extract the random effects from the fitted gam object which is returned as I'm interested to know how dynamics vary between subjects. I'm aware that specifying the random effect using s() with bs="re", is "dummying" a random effect, but I'm not sure if it is still possible to extact the random effects levels using this method? Thanks for your help, Louise -- View this message in context: http://r.789695.n4.nabble.com/mgcv-bam-prediction-levels-for-random-effects-tp4195614p4195614.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.
