logLik.gam {mgcv}R Documentation

Extract the log likelihood for a fitted GAM


Function to extract the log-likelihood for a fitted gam model (note that the models are usually fitted by penalized likelihood maximization).


## S3 method for class 'gam':


object fitted model objects of class gam as produced by gam().
... un-used in this case


Modification of logLik.glm which corrects the degrees of freedom for use with gam objects.

The function is provided so that AIC functions correctly with gam objects, and uses the appropriate degrees of freedom (accounting for penalization). Note, when using AIC for penalized models, that the degrees of freedom are the effective degrees of freedom and not the number of parameters, and the model maximizes the penalized likelihood, not the actual likelihood! This seems to be reasonably well founded for the known scale parameter case (see Hastie and Tibshirani, 1990, section 6.8.3), and in fact in this case the default smoothing parameter estimation criterion is effectively this modified AIC.


Standard logLik object: see logLik.


Simon N. Wood simon.wood@r-project.org based directly on logLik.glm


Hastie and Tibshirani, 1990, Generalized Additive Models.

See Also


[Package mgcv version 1.3-23 Index]