Title: Joint Species Distribution Models
Imports: Rcpp (>= 1.0.0), graphics, stats, coda, corrplot
Suggests: knitr, raster, sp, rmarkdown, bookdown, testthat, boral
Description: Fits joint species distribution models ('jSDM')
in a hierarchical Bayesian framework (Warton et 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

Imports: Rcpp (>= 1.0.0), graphics, stats, coda, corrplot, stringi,
Suggests: knitr, kableExtra, raster, sp, rgdal, dplyr, rmarkdown,
bookdown, testthat, boral, Hmsc, BayesComm, snow, snowfall,
person("Jeanne", "Clément", , "jeanne.clement16@laposte.net", role = c("aut", "cre"),
person("Ghislain", "Vieilledent", , "ghislain.vieilledent@cirad.fr", role = "aut",
person("Frédéric", "Gosselin", , "frederic.gosselin@inrae.fr", role = "ctb",
Author: Jeanne Clément [aut, cre] (<https://orcid.org/0000-0002-5228-5015>),

Title: Calculates the j-Score Between Two Clustering Assignments
c(person("Navid", "Ahmadinejad", email = "navidfr@asu.edu", role = c("cre","aut")),
person("Li", "Liu", email = "liliu@asu.edu", role = "aut"))
Description: The jscore() function in the package calculates the J-Score metric between two clustering
assignments. The score is designed to address some problems with existing common metrics such
as problem of matching. The details of J-score is described in Ahmadinejad and Liu. (2021) <arXiv:2109.01306>.

Title: jSonar Analytics Platform API for R
Description: This package enables users to access MongoDB by running queries
and returning their results in R data frames. Usually, data in MongoDB is
only available in the form of a JSON document. jSonarR uses data
processing and conversion capabilities in the jSonar Analytics Platform
and the JSON Studio Gateway (http://www.jsonstudio.com), to convert it to
a tabular format which is easy to use with existing R packages.

Depends: R (>= 2.12.1), RCurl, jsonlite, methods

Title: Jaatha - A Fast Parameter Estimation Method for Evolutionary
Author: Lisha Mathew, Paul R. Staab and Dirk Metzler
Maintainer: Paul R. Staab <staab@biologie.uni-muenchen.de>
Contact: Paul R. Staab <staab@biologie.uni-muenchen.de>
Description: Jaatha is a composite likelihood method for inferring
evolutionary parameters using genetic data. Given a model of
the evolutionary history of two biological populations as well
as SNP data from multiple individuals from each population, it
estimates model parameters like the time of separation of both
Depends: methods, foreach, phyclust (>= 0.1-14), ape, Rcpp