Hi,
Just getting into using GAM using the mgcv package. I've generated some
models and extracted the splines for each of the variables and started
visualizing them. I'm noticing that one of my variables is physically
unrealistic.
In the example below, my interpretation of the following plot is that the
y-axis is basically the equivalent of a "parameter" value of a GLM; in GAM
this value can change as the functional relationship changes between x and
y. In my case, I am predicting snowdepth based on the fractional snow
covered area. In no case will snowdepth realistically decrease for a unit
increase in fsca so my question is: *Is there a way to constrain the spline
to positive values? *
Thanks
Dominik
library(mgcv)
library(dplyr)
library(ggplot2)
extract_splines=function(mdl){
sterms=predict(mdl,type='terms')
datplot=cbind(sterms,mdl$model) %>% tbl_df
datplot$intercept=attr(sterms,'constant')
datplot$yhat=rowSums(sterms)+attr(sterms,'constant')
return(datplot)
}
dat=data_frame(snowdepth=runif(100,min =
0.001,max=6.7),fsca=runif(100,0.01,.99))
mdl=gam(snowdepth~s(fsca),data=dat)
termdF=extract_splines(mdl)
ggplot(termdF)+
geom_line(aes(x=fsca,y=`s(fsca)`))
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