VGAM: Vector Generalized Linear and Additive Models

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.

Version: 1.1-11
Depends: R (≥ 4.0.0), methods, stats, stats4, splines
Suggests: VGAMextra, MASS, mgcv
Enhances: VGAMdata
Published: 2024-05-15
DOI: 10.32614/CRAN.package.VGAM
Author: Thomas Yee ORCID iD [aut, cre], Cleve Moler [ctb] (LINPACK routines in src)
Maintainer: Thomas Yee <t.yee at>
License: GPL-3
NeedsCompilation: yes
Citation: VGAM citation info
Materials: NEWS ChangeLog
In views: Distributions, Econometrics, Environmetrics, ExtremeValue, Psychometrics, Survival
CRAN checks: VGAM results


Reference manual: VGAM.pdf


Package source: VGAM_1.1-11.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): VGAM_1.1-11.tgz, r-oldrel (arm64): VGAM_1.1-11.tgz, r-release (x86_64): VGAM_1.1-11.tgz, r-oldrel (x86_64): VGAM_1.1-11.tgz
Old sources: VGAM archive

Reverse dependencies:

Reverse depends: AnaCoDa, BayesGOF, deepSNV, DIFtree, EffectStars, EurosarcBayes, monocle, ordDisp, r3Cseq, regclass, rxSeq, svyVGAM, TBFmultinomial, VGAMdata, VGAMextra
Reverse imports: AICcmodavg, assessor, AutoTransQF, Bayenet, bayesCureRateModel, binspp, BioPET, CAGEr, CalcThemAll.PRM, calibmsm, Cascade, casebase, casper, cg, childsds, cicero, ClusPred, collin, CompDist, corncob, Countr, crlmm, crov, DEsingle, difNLR, discFA, discSurv, DPBBM, Dpit, drord, dwp, EffectStars2, eoa3, EpiForsk, ERPeq, fiberLD, fitPS, fmx, ForestGapR, FRASER, GeoModels, GJRM, glm.predict, glmxdiag, GlobalAncova, gofcat, ib, iccCounts, jmdem, JWileymisc, l1ball, lefko3, list, MADSEQ, marp, MigConnectivity, mixvlmc, multgee, netmediate, new.dist, orders, PAFit, PAsso, Patterns, ph2bye, PLreg, powerTCR, proteus, PScr, PureCN, RCM, refitME, RelDists, renz, robmixglm, rSHAPE, sads, sampleSelection, scMET, scRepertoire, scShapes, semisup, signeR, SimCorrMix, SimMultiCorrData, SLTCA, smcfcs, SOMNiBUS, sparsereg, ssdtools, sssc, TempStable, tpn, TPP, uSORT, vanquish, ZINAR1, zipfextR
Reverse suggests: adaptDiag, brglm2, broom.helpers, cardelino, catdata, copula, cubfits, DescTools, ecostats, ExtDist, extraDistr, familiar, flowml, ggeffects, giniVarCI, grandR, Hmisc, hnp, insight, isdals, kyotil, medflex, mediation, modeest, mvord, occupancy, ordinalNet, parameters, partDSA, performance, ppcc, qra, rms, robustrank, sageR, scMitoMut, serp, Seurat, ShinyItemAnalysis, singleRcapture, Sofi, sure, vcdExtra, wrMisc
Reverse enhances: prediction, skellam, texreg


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