Package: bpnreg 2.0.3
bpnreg: Bayesian Projected Normal Regression Models for Circular Data
Fitting Bayesian multiple and mixed-effect regression models for circular data based on the projected normal distribution. Both continuous and categorical predictors can be included. Sampling from the posterior is performed via an MCMC algorithm. Posterior descriptives of all parameters, model fit statistics and Bayes factors for hypothesis tests for inequality constrained hypotheses are provided. See Cremers, Mulder & Klugkist (2018) <doi:10.1111/bmsp.12108> and Nuñez-Antonio & Guttiérez-Peña (2014) <doi:10.1016/j.csda.2012.07.025>.
Authors:
bpnreg_2.0.3.tar.gz
bpnreg_2.0.3.tar.gz(r-4.5-noble)bpnreg_2.0.3.tar.gz(r-4.4-noble)
bpnreg_2.0.3.tgz(r-4.4-emscripten)bpnreg_2.0.3.tgz(r-4.3-emscripten)
bpnreg.pdf |bpnreg.html✨
bpnreg/json (API)
NEWS
# Install 'bpnreg' in R: |
install.packages('bpnreg', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/joliencremers/bpnreg/issues
Last updated 11 months agofrom:5c3b0d1853. Checks:OK: 2. Indexed: no.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Dec 11 2024 |
R-4.5-linux-x86_64 | OK | Dec 11 2024 |
Exports:BFcbpnmebpnrcoef_circcoef_lincoef_ranfithpd_esthpd_est_circmean_circmode_estmode_est_circrho_circsd_circtraceplot
Dependencies:BHbitbit64clicliprcpp11crayonfansiforcatsgluehavenhmslifecyclemagrittrpillarpkgconfigprettyunitsprogressR6RcppRcppArmadilloreadrrlangtibbletidyselecttzdbutf8vctrsvroomwithr