Vector Generalized Linear and Additive Models
Description
An implementation of about 6 major classes of
statistical regression models. At the heart of it are the
vector generalized linear and additive model (VGLM/VGAM)
classes. Many (150+) models and distributions are estimated
by maximum likelihood estimation (MLE) or penalized MLE, using
Fisher scoring. VGLMs can be loosely thought of as multivariate
GLMs. VGAMs are data-driven VGLMs (i.e., with smoothing). The
other classes are RR-VGLMs (reduced-rank VGLMs), quadratic
RR-VGLMs, reduced-rank VGAMs, RCIMs (row-column interaction
models)---these classes perform constrained and unconstrained
quadratic ordination (CQO/UQO) models in ecology, as well
as constrained additive ordination (CAO). Note that these
functions are subject to change, especially before version
1.0.0 is released; see the NEWS file for latest changes.