getFamily: Helper function for glmModelData: Extracts an S3 family...

In hypergsplines: Bayesian model selection with penalised splines and hyper-g prior

Description

Extracts an S3 family object, which (at least) the usual elements "family", "link", "linkfun", "linkinv", "variance", "mu.eta", "dev.resids", plus the additional elements: "phi" which includes just the dispersion parameter to be used, and "simulate" which can generate random variates for a given linear predictor and weight vector (this function of course also uses the "phi" value)

Usage

  getFamily(family, phi)

Arguments

family	the family argument passed to glmModelData
phi	the dispersion argument passed to glmModelData

Value

The returned family object also includes a custom ‘init’ function, which takes the response vector (or matrix) (‘y’) and the corresponding weight vector (‘weights’), processes them to response vector ‘y’ and possibly altered weights ‘weights’, and includes starting values ‘mustart’ for the IWLS algorithm. For example, here the binomial special case of two-column-response matrix is treated exactly in the same way as in glm.

hypergsplines documentation built on May 2, 2019, 6:14 p.m.