jSDM0.2.6 package

Joint Species Distribution Models

get_enviro_cor

Extract covariances and correlations due to shared environmental respo...

get_residual_cor

Calculate the residual correlation matrix from a latent variable model...

inv_logit

Generalized inverse logit function

jSDM-package

joint species distribution models

jSDM_binomial_logit

Binomial logistic regression

jSDM_binomial_probit

Binomial probit regression

jSDM_binomial_probit_long_format

Binomial probit regression on long format data

jSDM_binomial_probit_sp_constrained

Binomial probit regression with selected constrained species

jSDM_gaussian

Binomial probit regression

jSDM_poisson_log

Poisson regression with log link function

logit

Generalized logit function

plot_associations

plot_associations plot species-species associations

plot_residual_cor

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

predict.jSDM

Predict method for models fitted with jSDM

Download source packageRead PDF manual

Fits joint species distribution models ('jSDM') in a hierarchical Bayesian framework (Warton and al. 2015 <doi:10.1016/j.tree.2015.09.007>). The Gibbs sampler is written in 'C++'. It uses 'Rcpp', 'Armadillo' and 'GSL' to maximize computation efficiency.

  • Maintainer: Jeanne Clément
  • License: GPL-3
  • Last published: 2023-07-22

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