family.mgcv {mgcv}R Documentation

Distribution families in mgcv


As well as the standard families documented in family (see also glm) which can be used with functions gam, bam and gamm, mgcv also supplies some extra families, most of which are currently only usable with gam, although some can also be used with bam. These are described here.


The following families are in the exponential family given the value of a single parameter. They are usable with all modelling functions.

The following families are for regression type models dependent on a single linear predictor, and with a log likelihood which is a sum of independent terms, each coprresponding to a single response observation. Usable with gam, with smoothing parameter estimation by "REML" or "ML" (the latter does not integrate the unpenalized and parameteric effects out of the marginal likelihood optimized for the smoothing parameters). Also usable with bam.

The following families implement more general model classes. Usable only with gam and only with REML smoothing parameter estimation.


Simon N. Wood ( & Natalya Pya


Wood, S.N., N. Pya and B. Saefken (2016), Smoothing parameter and model selection for general smooth models. Journal of the American Statistical Association 111, 1548-1575

[Package mgcv version 1.8-28 Index]