R’s glm function for generalized linear modeling is very powerful and flexible: it supports all of the standard model types (binomial/logistic, Gamma, Poisson, etc.) and in fact you can fit any distribution in the exponential family (with the family argument). But if you want to use it on a data set with millions or rows, and especially with more than a couple of dozen variables (or even just a few categorical variables with many levels), this is a big computational task that quickly grows in time as the data gets larger, or even exhaust the available memory. The rxGlm function…
David Smith