VGAM: Vector Generalized Linear and Additive Models

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, and 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 VGAM package. Currently only fixed-effects models are implemented, i.e., no random-effects models. 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; see the NEWS and ChangeLog files for latest changes.

Version: 1.0-5
Depends: R (≥ 3.4.0), methods, stats, stats4, splines
Suggests: VGAMdata, MASS, mgcv
Published: 2018-02-07
Author: Thomas W. Yee
Maintainer: Thomas Yee <t.yee at auckland.ac.nz>
License: GPL-3
URL: https://www.stat.auckland.ac.nz/~yee/VGAM
NeedsCompilation: yes
Citation: VGAM citation info
Materials: NEWS ChangeLog
In views: Distributions, Econometrics, Environmetrics, ExtremeValue, Multivariate, Psychometrics, SocialSciences, Survival
CRAN checks: VGAM results

Downloads:

Reference manual: VGAM.pdf
Vignettes: The VGAM Package for Categorical Data Analysis
The VGAM Package for Capture–Recapture Data Using the Conditional Likelihood
Package source: VGAM_1.0-5.tar.gz
Windows binaries: r-devel: VGAM_1.0-5.zip, r-release: VGAM_1.0-5.zip, r-oldrel: VGAM_1.0-3.zip
OS X El Capitan binaries: r-release: VGAM_1.0-5.tgz
OS X Mavericks binaries: r-oldrel: VGAM_1.0-3.tgz
Old sources: VGAM archive

Reverse dependencies:

Reverse depends: BayesGOF, Bayesthresh, BSquare, EffectStars, errint, EurosarcBayes, GEVcdn, iteRates, lawstat, multgee, ordBTL, ordDisp, pheno2geno, regclass, rxSeq, TBFmultinomial
Reverse imports: AICcmodavg, BioPET, casebase, cg, CompDist, Countr, DAMisc, DPBBM, Dpit, EffectStars2, ExomeDepth, fakeR, GJRM, gmediation, HiDimMaxStable, hmi, ldstatsHD, list, lllcrc, misreport, moezipfR, PAFit, ph2bye, poweRlaw, sads, sampleSelection, SemiParSampleSel, Seurat, SimMultiCorrData, smcfcs, snowboot, SparseFactorAnalysis, sparsereg, spatialwarnings, staTools, Wrapped, Zelig, ZeligChoice
Reverse suggests: AnaCoDa, catdata, copula, cubfits, DeLorean, discSurv, hnp, isdals, kyotil, medflex, mediation, mlt.docreg, mnlogit, modeest, ordinalNet, partDSA, ppcc, robustrank, skellam, Sofi, sure, tscount, vcdExtra, VGAMdata
Reverse enhances: prediction, texreg

Linking:

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