Hi,
I'm working with step.gam in gam package. I'm interested both in spline and
lowess functions and when I define all the models that I'm interested in I get
something like that:
> gam.object.ALC<-gam(X143S~ALC,data=dane,family=binomial)
>
step.gam.ALC<-step.gam(gam.object.ALC,scope=list("ALC"=~1+ALC+s(ALC,2)+s(ALC,3)+s(ALC,4)+s(ALC,6)+s(ALC,8)+lo(ALC,degree=1,span=.5)+lo(ALC,degree=2,span=.5)+lo(ALC,degree=1,span=.25)+lo(ALC,degree=2,span=.25)))
Start: X143S ~ ALC; AIC= 104.0815
Trial: X143S ~ 1; AIC= 111.1054
Trial: X143S ~ s(ALC, 2); AIC= 103.3325
Step : X143S ~ s(ALC, 2) ; AIC= 103.3325
Trial: X143S ~ s(ALC, 3); AIC= 102.9598
Step : X143S ~ s(ALC, 3) ; AIC= 102.9598
Trial: X143S ~ s(ALC, 4); AIC= 102.2103
Step : X143S ~ s(ALC, 4) ; AIC= 102.2103
Trial: X143S ~ s(ALC, 6); AIC= 102.4548
I have impression that the algorithm stops when the next trial gives higher AIC
without examining further functions. When I deleted some of the spline functions
that were worse than s(ALC,4) I got:
>
step.gam.ALC<-step.gam(gam.object.ALC,scope=list("ALC"=~1+ALC++s(ALC,4)+lo(ALC,degree=1,span=.5)+lo(ALC,degree=2,span=.5)+lo(ALC,degree=1,span=.25)+lo(ALC,degree=2,span=.25)))
Start: X143S ~ ALC; AIC= 104.0815
Trial: X143S ~ 1; AIC= 111.1054
Trial: X143S ~ s(ALC, 4); AIC= 102.2103
Step : X143S ~ s(ALC, 4) ; AIC= 102.2103
Trial: X143S ~ lo(ALC, degree = 1, span = 0.5); AIC= 99.8127
Step : X143S ~ lo(ALC, degree = 1, span = 0.5) ; AIC= 99.8127
Trial: X143S ~ lo(ALC, degree = 2, span = 0.5); AIC= 100.5275
Lowess turned out to be better in this situation. Is there any way to examine
all the models without stopping when AIC is higher in the next trial? Or maybe
manual handling is the only solution?
thanks for help in advance
Agnieszka Strzelczak
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