The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.

gllvm: Generalized Linear Latent Variable Models

Analysis of multivariate data using generalized linear latent variable models (gllvm). Estimation is performed using either the Laplace method, variational approximations, or extended variational approximations, implemented via TMB (Kristensen et al. (2016), <doi:10.18637/jss.v070.i05>).

Version: 2.0
Depends: R (≥ 3.5.0), TMB
Imports: MASS, Matrix, statmod, fishMod, mgcv, alabama, nloptr, methods
LinkingTo: TMB, RcppEigen
Suggests: knitr, rmarkdown, testthat, gclus, corrplot, lattice, mvabund, ape, parallel
Published: 2024-11-26
DOI: 10.32614/CRAN.package.gllvm
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://jenniniku.github.io/gllvm/, 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 (source, R code)
Analysing high-dimensional microbial community data using gllvm (source, R code)
Introduction to gllvm Part 1: Ordination (source, R code)
Introduction to gllvm Part 2: Species correlations (source, R code)
How to use the quadratic response model (source, R code)
Ordination with predictors (source)
Phylogenetic random effects (source)
Analysing sparse ecological percent cover data using gllvm (source, R code)
Correlation structures for latent variables and row effects (source)

Downloads:

Package source: gllvm_2.0.tar.gz
Windows binaries: r-devel: gllvm_2.0.zip, r-release: gllvm_2.0.zip, r-oldrel: gllvm_2.0.zip
macOS binaries: r-release (arm64): gllvm_2.0.tgz, r-oldrel (arm64): gllvm_2.0.tgz, r-release (x86_64): gllvm_2.0.tgz, r-oldrel (x86_64): gllvm_2.0.tgz
Old sources: gllvm archive

Reverse dependencies:

Reverse suggests: ecostats

Linking:

Please use the canonical form https://CRAN.R-project.org/package=gllvm to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.