Package: ubms Version: 1.2.6 Date: 2023-09-11 Title: Bayesian Models for Data from Unmarked Animals using 'Stan' Authors@R: person("Ken", "Kellner", email="contact@kenkellner.com", role=c("cre","aut")) Depends: R (>= 3.4.0), unmarked Imports: ggplot2 (>= 2.0.0), gridExtra, lme4, loo, Matrix (>= 1.5-0), methods, pbapply, Rcpp (>= 0.12.0), rlang, RSpectra, rstan (>= 2.26.0), rstantools (>= 2.0.0), stats Suggests: covr, devtools, knitr, pkgdown, raster, rmarkdown, roxygen2, testthat VignetteBuilder: knitr Description: Fit Bayesian hierarchical models of animal abundance and occurrence via the 'rstan' package, the R interface to the 'Stan' C++ library. Supported models include single-season occupancy, dynamic occupancy, and N-mixture abundance models. Covariates on model parameters are specified using a formula-based interface similar to package 'unmarked', while also allowing for estimation of random slope and intercept terms. References: Carpenter et al. (2017) ; Fiske and Chandler (2011) . License: GPL (>=3) URL: https://kenkellner.com/ubms/ BugReports: https://github.com/kenkellner/ubms/issues Encoding: UTF-8 RoxygenNote: 7.2.2 Biarch: true LinkingTo: BH (>= 1.66.0), Rcpp (>= 0.12.0), RcppArmadillo (>= 0.9.300.2.0), RcppEigen (>= 0.3.3.3.0), rstan (>= 2.26.0), StanHeaders (>= 2.26.0), RcppParallel (>= 5.0.2) SystemRequirements: GNU make Collate: 'RcppExports.R' 'submodel.R' 'response.R' 'inputs.R' 'fit.R' 'posterior_predict.R' 'posterior_linpred.R' 'fitted.R' 'gof.R' 'occu.R' 'colext.R' 'missing.R' 'distsamp.R' 'fitlist.R' 'kfold.R' 'occuTTD.R' 'multinomPois.R' 'occuRN.R' 'pcount.R' 'loglik.R' 'mb_chisq.R' 'plot_effects.R' 'plot_posteriors.R' 'predict.R' 'priors.R' 'ranef.R' 'residuals.R' 'spatial.R' 'stanmodels.R' 'test-helpers.R' 'ubms-package.R' 'ubmsFit-methods.R' 'ubmsFitList-methods.R' 'umf.R' 'utils.R'