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Hmsc  

Hierarchical Model of Species Communities
View on CRAN: Click here


Download and install Hmsc package within the R console
Install from CRAN:
install.packages("Hmsc")

Install from Github:
library("remotes")
install_github("cran/Hmsc")

Install by package version:
library("remotes")
install_version("Hmsc", "3.0-13")



Attach the package and use:
library("Hmsc")
Maintained by
Otso Ovaskainen
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-10-13
Latest Update: 2022-08-11
Description:
Hierarchical Modelling of Species Communities (HMSC) is a model-based approach for analyzing community ecological data. This package implements it in the Bayesian framework with Gibbs Markov chain Monte Carlo (MCMC) sampling (Tikhonov et al. (2020) ).
How to cite:
Otso Ovaskainen (2019). Hmsc: Hierarchical Model of Species Communities. R package version 3.0-13, https://cran.r-project.org/web/packages/Hmsc
Previous versions and publish date:
3.0-2 (2019-10-13 16:00), 3.0-4 (2019-12-16 13:50), 3.0-6 (2020-03-19 12:30), 3.0-9 (2020-10-29 18:30), 3.0-11 (2021-02-24 10:50)
Other packages that cited Hmsc R package
View Hmsc citation profile
Other R packages that Hmsc depends, imports, suggests or enhances
Functions, R codes and Examples using the Hmsc R package
Some associated functions: Hmsc-package . Hmsc . HmscRandomLevel . TD . alignPosterior . biPlot . c.Hmsc . computeAssociations . computeDataParameters . computeInitialParameters . computePredictedValues . computeVariancePartitioning . computeWAIC . constructGradient . constructKnots . convertToCodaObject . createPartition . evaluateModelFit . getPostEstimate . plotBeta . plotGamma . plotGradient . plotVariancePartitioning . poolMcmcChains . predict.Hmsc . predictLatentFactor . prepareGradient . sampleMcmc . samplePrior . setPriors.Hmsc . setPriors.HmscRandomLevel . setPriors . 
Some associated R codes: Hmsc.R . HmscRandomLevel.R . alignPosterior.R . biPlot.R . c.Hmsc.R . combineParameters.R . computeAssociations.R . computeDataParameters.R . computeInitialParameters.R . computePredictedValues.R . computePredictedValuesParallel.R . computeVariancePartitioning.R . computeWAIC.R . constructGradient.R . constructKnots.R . createPartition.R . data.R . evaluateModelFit.R . getPostEstimate.R . plotBeta.R . plotGamma.R . plotGradient.R . plotVariancePartitioning.R . poolMcmcChains.R . predict.R . predictLatentFactor.R . prepareGradient.R . print.Hmsc.R . print.HmscRandomLevel.R . sampleMcmc.R . samplePrior.R . setPriors.Hmsc.R . setPriors.HmscRandomLevel.R . setPriors.R . updateAlpha.R . updateBetaLambda.R . updateBetaSel.R . updateEta.R . updateGamma2.R . updateGammaEta.R . updateGammaV.R . updateInvSigma.R . updateLambdaPriors.R . updateLatentLoadingOrder.R . updateNf.R . updateRho.R . updateZ.R . updatewRRR.R . updatewRRRPriors.R .  Full Hmsc package functions and examples
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