VGAM

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 data-driven VGLMs that use smoothing. The book "Vector Generalized Linear and Additive Models: With an Implementation in R" (Yee, 2015) doi:10.1007/978-1-4939-2818-7 gives details of the statistical framework and the package. Currently only fixed-effects models are implemented. Many (100+) models and distributions are estimated by maximum likelihood estimation (MLE) or penalized MLE. The other classes are RR-VGLMs (reduced-rank VGLMs), quadratic RR-VGLMs, doubly constrained RR-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). Hauck-Donner effect detection is implemented. Note that these functions are subject to change; see the NEWS and ChangeLog files for latest changes.

Last 30 days

This package has been downloaded 42,532 times in the last 30 days. That's enough downloads to make it mildly famous in niche technical communities. A badge of honor! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 1,566 times.

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Last 365 days

This package has been downloaded 475,663 times in the last 365 days. Practically an academic rockstar! That's enough downloads to cause murmurs at international conferences. The day with the most downloads was Feb 17, 2025 with 4,689 downloads.

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