- New function
`jSDM_gaussian`

for fitting joint species distribution models from continuous Gaussian data, including an overdispersion parameter. - Use of the R package
`terra`

instead of`raster`

and`sp`

, which are depreciated, in the vignette Estimation of Madagascar’s plant biodiversity.

- Add the possibility to consider only significant correlations in the
`get_residual_cor`

and`plot_residual_cor`

functions. - Documentation correction

- New function
`jSDM_binomial_probit_sp_constrained`

which aims to improve the convergence of latent variable models fitting by selecting the species constrained to have positive values of factor loadings \(\lambda\) and new vignette Bernoulli probit regression with selected constrained species to illustrate its use. - New vignette Estimation of Madagascar’s plant biodiversity available.

- Add the possibility of considering an additional hierarchical level
in the Bayesian models of the
`jSDM_binomial_probit`

,`jSDM_binomial_logit`

and`jSDM_poisson_log`

functions to take into account interactions between species-specific traits and the environment in estimating species effects. - New vignette Bernoulli probit regression including species traits available.
- Separate the drawing of species effects beta and factor loading
lambda in the functions
`jSDM_binomial_probit_block`

and`jSDM_binomial_probit_block_long_format`

renamed`jSDM_binomial_probit`

and`jSDM_binomial_probit_long_format`

. - New function
`plot_associations`

to plot species-species associations.

- Use of
`roxygen2`

for documentation and NAMESPACE - Rename
`jSDM_binomial_probit_block`

the function`jSDM_probit_block`

. - New function
`jSDM_binomial_probit_block_long_format`

for fitting joint species distribution models from presence-absence data in long format able to handle missing observations, multiple visits at sites and to integer species traits as explanatory variables.

- New function
`jSDM_poisson_log`

for fitting joint species distribution models from abundance data inspired by Hui and Francis K. C. 2016*Methods in Ecology and Evolution*(doi:10.1111/2041-210X.12514). - New function
`jSDM_binomial_logit`

for fitting joint species distribution models from presence-absence data at multiple-visited sites using a bayesian inference method inspired by Albert, James H. and Chib Siddhartha 1993*Journal of the American Statistical Association*(doi:10.1080/01621459.1993.10476321). - Functions to fit models in which site effects are included as fixed effects, as random effects or not included and with or without latent variables.
- New function
`get_enviro_cor`

to extract covariances and correlations due to shared environmental responses. - Complete
`jSDM-package`

documentation - Add datasets (
`mosquitos`

,`fungi`

,`eucalypts`

,`birds`

,`mites`

,`aravo`

). - Seven new vignettes (Bayesian inference methods, Poisson log-linear regression, Bernoulli probit regression, Bernoulli probit regression with missing data and species traits, Binomial logistic regression, Running jSDM in parallel, Comparing SDMs and JSDMs and Comparison jSDM-Hmsc) are available.
- Complete and correct the vignette Comparison jSDM-boral.
- Add Code of conduct and Contributing section

- New package website available on GitHub: https://ecology.ghislainv.fr/jSDM/.

- First version of the jSDM R package
- Use of Rcpp and C++ code for Gibbs sampling
- Use of GSL (RcppGSL) for random draws
- Use of Armadillo (RcppArmadillo) for vector and matrix operations
- Functions to fit models from Warton et al. 2014
*Trends in Ecology and Evolution*(doi:10.1016/j.tree.2015.09.007). - We use
`pkgdown`

to build package website. - Package website available on GitHub: https://ecology.ghislainv.fr/jSDM/.