Package: gllvm 2.0.9
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>).
Authors:
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gllvm.pdf |gllvm.html✨
gllvm/json (API)
NEWS
| # Install 'gllvm' in R: |
| install.packages('gllvm', repos = c('https://jenniniku.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/jenniniku/gllvm/issues
Pkgdown/docs site:https://jenniniku.github.io
- beetle - Ground beetle assemblages
- eSpider - Hunting spider data
- fungi - Wood-decaying fungi data
- kelpforest - Kelp Forest community Dynamics: Cover of sessile organisms, Uniform Point Contact
- microbialdata - Microbial community data
- Skabbholmen - Skabbholmen island data
Last updated from:d7f698a641. Checks:11 ERROR, 2 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | ERROR | 447 | ||
| linux-devel-x86_64 | ERROR | 438 | ||
| source / vignettes | OK | 597 | ||
| linux-release-arm64 | ERROR | 416 | ||
| linux-release-x86_64 | ERROR | 375 | ||
| macos-release-arm64 | ERROR | 434 | ||
| macos-release-x86_64 | ERROR | 768 | ||
| macos-oldrel-arm64 | ERROR | 288 | ||
| macos-oldrel-x86_64 | ERROR | 687 | ||
| windows-devel | ERROR | 577 | ||
| windows-release | ERROR | 506 | ||
| windows-oldrel | ERROR | 582 | ||
| wasm-release | OK | 209 |
Exports:AICcAICc.gllvmcoefplotcoefplot.gllvmconfint.gllvmgetEnvironCorgetEnvironCor.gllvmgetEnvironCovgetEnvironCov.gllvmgetLoadingsgetLoadings.gllvmgetLVgetLV.gllvmgetPredictErrgetPredictErr.gllvmgetResidualCorgetResidualCor.gllvmgetResidualCovgetResidualCov.gllvmgllvmglmmVAgoodnessOfFitlogLik.gllvmnobs.gllvmoptimaoptima.gllvmordiplotordiplot.gllvmphyloplotphyloplot.gllvmplotVarPartitioningplotVPpredict.gllvmpredictLVspredictLVs.gllvmpredictPairwisepredictPairwise.gllvmpredictSRpredictSR.gllvmprint.summary.gllvmprint.VP.gllvmrandomCoefplotrandomCoefplot.gllvmresiduals.predictSR.gllvmsese.gllvmsimulatesimulate.gllvmtolerancestolerances.gllvmupdate.gllvmvarPartitioningvarPartitioning.gllvmvcov.gllvmVP
Dependencies:alabamafishModlatticeMASSMatrixmgcvnlmenloptrnumDerivRcppRcppEigenTMB
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Rendered fromvignette2.rmdusingknitr::rmarkdownon Apr 15 2026.Last update: 2025-03-28
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Assessing Convergence in gllvm models
Rendered fromvignette10.Rmdusingknitr::rmarkdownon Apr 15 2026.Last update: 2026-04-01
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Correlation structures for latent variables and row effects
Rendered fromvignette9.Rmdusingknitr::rmarkdownon Apr 15 2026.Last update: 2025-03-31
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How to use the quadratic response model
Rendered fromvignette5.Rmdusingknitr::rmarkdownon Apr 15 2026.Last update: 2024-09-06
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Introduction to gllvm Part 1: Ordination
Rendered fromvignette3.rmdusingknitr::rmarkdownon Apr 15 2026.Last update: 2024-11-20
Started: 2020-12-14
Introduction to gllvm Part 2: Species correlations
Rendered fromvignette4.rmdusingknitr::rmarkdownon Apr 15 2026.Last update: 2024-11-20
Started: 2020-12-14
Ordination with predictors
Rendered fromvignette6.Rmdusingknitr::rmarkdownon Apr 15 2026.Last update: 2025-02-28
Started: 2021-07-01
Phylogenetic random effects
Rendered fromvignette7.Rmdusingknitr::rmarkdownon Apr 15 2026.Last update: 2024-11-25
Started: 2024-09-06
