Dear R-users,
To obtain the percentage of deviance explained when fitting a gam model using
the mgcv library is straightforward:
summary(object.gam) $dev.expl
or alternatively, using the deviance (deviance(object.gam)) of the null and the
fitted models, and then using 1 minus the quotient of deviances.
However, when a gamm (generalizad aditive mixed model) is fitted, the deviance
is not displayed, and only the logLik of the underlying lme model can be
derived (logLik(objetct.gamm$lme)), which is not enough to derive the
percentage deviance explained because the logLik for the saturated model is not
available.
Any suggestions on how to obtain the deviance explained when a gamm is fitted
when the typical default gauusian model is fitted? Or alternavely, are the R^2
derived from a gam model and a gamm model comparable?
Thanks a lot in advance,
Berta
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