An implementation of about 6 major classes of statistical regression models. The central algorithm is Fisher scoring and iterative reweighted least squares. At the heart of this package are the vector generalized linear and additive model (VGLM/VGAM) classes. VGLMs can be loosely thought of as multivariate GLMs. VGAMs are datadriven VGLMs that use smoothing. The book "Vector Generalized Linear and Additive Models: With an Implementation in R" (Yee, 2015) <DOI:10.1007/9781493928187> gives details of the statistical framework and the package. Currently only fixedeffects models are implemented. Many (100+) models and distributions are estimated by maximum likelihood estimation (MLE) or penalized MLE. The other classes are RRVGLMs (reducedrank VGLMs), quadratic RRVGLMs, reducedrank VGAMs, RCIMs (rowcolumn interaction models)these classes perform constrained and unconstrained quadratic ordination (CQO/UQO) models in ecology, as well as constrained additive ordination (CAO). HauckDonner effect detection is implemented. Note that these functions are subject to change; see the NEWS and ChangeLog files for latest changes.
Package details 


Author  Thomas Yee [aut, cre] (<https://orcid.org/0000000299703907>), Cleve Moler [ctb] (author of several LINPACK routines) 
Maintainer  Thomas Yee <t.yee@auckland.ac.nz> 
License  GPL3 
Version  1.19 
URL  https://www.stat.auckland.ac.nz/~yee/VGAM/ 
Package repository  View on CRAN 
Installation 
Install the latest version of this package by entering the following in R:

Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.