R help - May 2009 - Deviance explined in GAMM, library mgcv

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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Hi all, 

I have the same question for a GAMM with quasi-poisson errors.  Does anyone
know how to calculate the % deviance explained by a GAMM model or any other
method evaluating the % contribution of the model in explaining the response
variable (eg. number of birds in an area)?

Thanks

Nicole



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?


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