Package: gllvm 2.0
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:
gllvm_2.0.tar.gz
gllvm_2.0.tar.gz(r-4.5-noble)gllvm_2.0.tar.gz(r-4.4-noble)
gllvm_2.0.tgz(r-4.4-emscripten)gllvm_2.0.tgz(r-4.3-emscripten)
gllvm.pdf |gllvm.html✨
gllvm/json (API)
NEWS
# Install 'gllvm' in R: |
install.packages('gllvm', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/jenniniku/gllvm/issues
Pkgdown:https://jenniniku.github.io
- Skabbholmen - Skabbholmen island data
- 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
Last updated 12 days agofrom:9c0fd00ac8. Checks:OK: 2. Indexed: no.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 27 2024 |
R-4.5-linux-x86_64 | OK | Nov 27 2024 |
Exports:AICcAICc.gllvmcoefplotcoefplot.gllvmconfint.gllvmgetEnvironCorgetEnvironCor.gllvmgetEnvironCovgetEnvironCov.gllvmgetLoadingsgetLoadings.gllvmgetLVgetLV.gllvmgetPredictErrgetPredictErr.gllvmgetResidualCorgetResidualCor.gllvmgetResidualCovgetResidualCov.gllvmgllvmlogLik.gllvmnobs.gllvmoptimaoptima.gllvmordiplotordiplot.gllvmphyloplotphyloplot.gllvmplotVarPartitioningplotVPpredict.gllvmpredictLVspredictLVs.gllvmprint.summary.gllvmrandomCoefplotrandomCoefplot.gllvmsese.gllvmsimulatesimulate.gllvmtolerancestolerances.gllvmvarPartitioningvarPartitioning.gllvmvcov.gllvmVP
Dependencies:alabamafishModlatticeMASSMatrixmgcvnlmenloptrnumDerivRcppRcppEigenstatmodTMB
Analysing high-dimensional microbial community data using gllvm
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usingknitr::rmarkdown
on Nov 27 2024.Last update: 2024-11-26
Started: 2019-08-23
Analysing multivariate abundance data using gllvm
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usingknitr::rmarkdown
on Nov 27 2024.Last update: 2024-11-26
Started: 2019-08-23
Analysing sparse ecological percent cover data using gllvm
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usingknitr::rmarkdown
on Nov 27 2024.Last update: 2024-11-26
Started: 2024-11-26
Correlation structures for latent variables and row effects
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usingknitr::rmarkdown
on Nov 27 2024.Last update: 2024-11-26
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How to use the quadratic response model
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usingknitr::rmarkdown
on Nov 27 2024.Last update: 2024-11-26
Started: 2022-12-17
Introduction to gllvm Part 1: Ordination
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usingknitr::rmarkdown
on Nov 27 2024.Last update: 2024-11-26
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Introduction to gllvm Part 2: Species correlations
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usingknitr::rmarkdown
on Nov 27 2024.Last update: 2024-11-26
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Ordination with predictors
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usingknitr::rmarkdown
on Nov 27 2024.Last update: 2024-11-26
Started: 2022-12-17
Phylogenetic random effects
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usingknitr::rmarkdown
on Nov 27 2024.Last update: 2024-11-26
Started: 2024-11-26