family.mgcv {mgcv}R Documentation

Distribution families in mgcv


As well as the standard families (of class family) 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 (class family) are in the exponential family given the value of a single parameter. They are usable with all modelling functions.

The following families (class are for regression type models dependent on a single linear predictor, and with a log likelihood which is a sum of independent terms, each corresponding to a single response observation. Usable with gam, with smoothing parameter estimation by "NCV", "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 above families of class family and can be combined to model data where different response observations come from different distributions. For example, when modelling the combination of presence-absence and abundance data, binomial and nb families might be used.

The following families (class implement more general model classes. Usable only with gam and only with REML or NCV 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 doi:10.1080/01621459.2016.1180986

[Package mgcv version 1.9-1 Index]