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jSDM R Package

Package for fitting joint species distribution models (JSDM) in a hierarchical Bayesian framework (Warton et al. 2015). The Gibbs sampler is written in C++. It uses Rcpp, Armadillo and GSL to maximize computation efficiency.

System requirements

Make sure the GNU Scientific Library (GSL) is installed on your system.

Installation

Stable version from CRAN

Install the latest stable version of jSDM from CRAN with:

install.packages("jSDM")

Development version

Or install the development version of jSDM from GitHub with:

devtools::install_github("ghislainv/jSDM")

Or the binary release of jSDM’s development version compiled with R version 4.3.0 can be found here :

jSDM_windows.

Available functions

The package includes the following functions to fit various species distribution models :

functiondata typedata format
jSDM_binomial_logit()presence-absencewide
jSDM_binomial_probit()presence-absencewide
jSDM_binomial_probit_sp_constrained()presence-absencewide
jSDM_binomial_probit_long_format()presence-absencelong
jSDM_poisson_log()abundancewide
jSDM_gaussian()continuouswide

Contributing

The jSDM R package is Open Source and released under the GNU GPL version 3 license. Anybody who is interested can contribute to the package development following our Community guidelines. Every contributor must agree to follow the project’s Code of Conduct.

References

Warton, D.I., Blanchet, F.G., O’Hara, R.B., Ovaskainen, O., Taskinen, S., Walker, S.C. & Hui, F.K.C. (2015) So many variables: Joint modeling in community ecology. Trends in Ecology & Evolution, 30, 766–779.

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Version

Install

install.packages('jSDM')

Monthly Downloads

160

Version

0.2.6

License

GPL-3

Issues

Pull Requests

Stars

Forks

Maintainer

Jeanne Cl<c3><a9>ment

Last Published

July 22nd, 2023

Functions in jSDM (0.2.6)

jSDM-package

joint species distribution models
eucalypts

eucalypts dataset
frogs

frogs dataset
get_enviro_cor

Extract covariances and correlations due to shared environmental responses
aravo

Distribution of Alpine plants in Aravo (Valloire, France)
fungi

fungi dataset
get_residual_cor

Calculate the residual correlation matrix from a latent variable model (LVM)
jSDM_binomial_logit

Binomial logistic regression
birds

birds dataset
inv_logit

Generalized inverse logit function
jSDM_poisson_log

Poisson regression with log link function
logit

Generalized logit function
jSDM_gaussian

Binomial probit regression
jSDM_binomial_probit_sp_constrained

Binomial probit regression with selected constrained species
mites

mites dataset
madagascar

Madagascar's forest inventory
mosquitos

mosquitos dataset
plot_residual_cor

Plot the residual correlation matrix from a latent variable model (LVM).
predict.jSDM

Predict method for models fitted with jSDM
plot_associations

plot_associations plot species-species associations
jSDM_binomial_probit

Binomial probit regression
jSDM_binomial_probit_long_format

Binomial probit regression on long format data