gllvm: Generalized Linear Latent Variable Models

Analysis of multivariate data using generalized linear latent variable models (gllvm). Estimation is performed using either Laplace approximation method or variational approximation method implemented via TMB (Kristensen et al., (2016), <doi:10.18637/jss.v070.i05>). For details see Niku et al. (2019a) <doi:10.1371/journal.pone.0216129> and Niku et al. (2019b) <doi:10.1111/2041-210X.13303>.

Version:	1.4.3
Depends:	R (≥ 3.5.0), TMB, mvabund
Imports:	MASS, Matrix, statmod, fishMod, mgcv, alabama, nloptr, methods
LinkingTo:	TMB, RcppEigen
Suggests:	knitr, rmarkdown, testthat, gclus, corrplot, lattice
Published:	2023-09-18
Author:	Jenni Niku [aut, cre], Wesley Brooks [aut], Riki Herliansyah [aut], Francis K.C. Hui [aut], Pekka Korhonen [aut], Sara Taskinen [aut], Bert van der Veen [aut], David I. Warton [aut]
Maintainer:	Jenni Niku <jenni.m.e.niku at jyu.fi>
BugReports:	https://github.com/JenniNiku/gllvm/issues
License:	GPL-2
URL:	https://github.com/JenniNiku/gllvm
NeedsCompilation:	yes
Citation:	gllvm citation info
Materials:	README NEWS
In views:	Environmetrics
CRAN checks:	gllvm results

Documentation:

Reference manual:	gllvm.pdf
Vignettes:	Analysing multivariate abundance data using gllvm Analysing high-dimensional microbial community data using gllvm Introduction to gllvm Part 1: Ordination Introduction to gllvm Part 2: Species correlations How to use the quadratic response model Ordination with predictors

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Package source:	gllvm_1.4.3.tar.gz
Windows binaries:	r-devel: gllvm_1.4.3.zip, r-release: gllvm_1.4.3.zip, r-oldrel: gllvm_1.4.3.zip
macOS binaries:	r-release (arm64): gllvm_1.4.3.tgz, r-oldrel (arm64): gllvm_1.4.3.tgz, r-release (x86_64): gllvm_1.4.3.tgz, r-oldrel (x86_64): gllvm_1.4.3.tgz
Old sources:	gllvm archive

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