You haven't given quite enough information to be sure, but I would guess that
this is not really a problem, but rather the interesting proporty of GLMs
fitted with a canonical link described in e.g. section 2.1.8 of Wood (2006)
Generalized additive models: and introduction with R, or at the beginning of
the GLM chapter in Venables and Ripley MASS.
On Friday 21 August 2009 22:03, Lucía Rueda wrote:
> Hi,
>
> I am comparing the observed and fitted values of my GAM model, which
> includes the explanatory variables: longitude, depth, ssh, year and month.
> When I compare observed and fitted values for longitude, depth and ssh it
> works. But when I try to do it for month and year (which are as factors in
> the GAM model) it doesn't work. My observed and fitted values are exactly
> the same.. How is that possible?� Thanks
>
> > Obs_factor1<-aggregate(x=albdata$turtles,by=list(albdata$Year),FUN=mean)
> > names(Obs_factor1)=c("Bin","Observed")
> > Obs_factor1
>
> ��� Bin��� Observed
> 1� 1997 0.017094017
> 2� 1998 0.010652463
> 3� 1999 0.023000000
> 4� 2000 0.017167382
> 5� 2001 0.030465950
> 6� 2002 0.007446809
> 7� 2003 0.010568032
> 8� 2004 0.011450382
> 9� 2005 0.016270338
> 10 2006 0.017006803
> 11 2007 0.030969031
> 12 2008 0.066455696
>
> > Fit_factor1<-aggregate(x=predict(gam.def.lon,type="response"),by=list(alb
> >data$Year),FUN=mean) names(Fit_factor1)=c("Bin","Fitted")
> > Fit_factor1
>
> ��� Bin����� Fitted
> 1� 1997 0.017094017
> 2� 1998 0.010652463
> 3� 1999 0.023000000
> 4� 2000 0.017167382
> 5� 2001 0.030465950
> 6� 2002 0.007446809
> 7� 2003 0.010568032
> 8� 2004 0.011450382
> 9� 2005 0.016270338
> 10 2006 0.017006803
> 11 2007 0.030969031
> 12 2008 0.066455696
>
>
>
>
>
>
> [[alternative HTML version deleted]]
--
> Simon Wood, Mathematical Sciences, University of Bath, Bath, BA2 7AY UK
> +44 1225 386603 www.maths.bath.ac.uk/~sw283
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