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:Jolien Cremers [aut, cre]

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bpnreg.pdf |bpnreg.html✨
bpnreg/json (API)
NEWS

# Install 'bpnreg' in R:
install.packages('bpnreg', repos = c('https://joliencremers.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/joliencremers/bpnreg/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library
Datasets:
  • Maps - The geometry of human knowledge of navigation space.
  • Motor - Phase differences in hand flexion-extension movements.

On CRAN:

6.13 score 13 stars 103 scripts 379 downloads 1 mentions 15 exports 30 dependencies

Last updated 1 years agofrom:1d32f5e9ac. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 25 2024
R-4.5-win-x86_64OKOct 25 2024
R-4.5-linux-x86_64OKOct 25 2024
R-4.4-win-x86_64OKOct 25 2024
R-4.4-mac-x86_64OKOct 25 2024
R-4.4-mac-aarch64OKOct 25 2024
R-4.3-win-x86_64OKOct 25 2024
R-4.3-mac-x86_64OKOct 25 2024
R-4.3-mac-aarch64OKOct 25 2024

Exports:BFcbpnmebpnrcoef_circcoef_lincoef_ranfithpd_esthpd_est_circmean_circmode_estmode_est_circrho_circsd_circtraceplot

Dependencies:BHbitbit64clicliprcpp11crayonfansiforcatsgluehavenhmslifecyclemagrittrpillarpkgconfigprettyunitsprogressR6RcppRcppArmadilloreadrrlangtibbletidyselecttzdbutf8vctrsvroomwithr

FAQ

Rendered fromFAQ.Rmdusingknitr::rmarkdownon Oct 25 2024.

Last update: 2021-03-09
Started: 2021-03-01

Readme and manuals

Help Manual

Help pageTopics
Bayes FactorsBFc
Bayes Factors for a Bayesian circular mixed-effects modelBFc.bpnme
Bayes Factors for a Bayesian circular regression modelBFc.bpnr
Fit a Bayesian circular mixed-effects modelbpnme
Fit a Bayesian circular regression modelbpnr
Compute circular coefficients from linear coefficientscirc_coef
Compute circular coefficientscirc_coef_rcpp
Circular coefficientscoef_circ
Obtain the circular coefficients of a Bayesian circular mixed-effects modelcoef_circ.bpnme
Obtain the circular coefficients of a Bayesian circular regression modelcoef_circ.bpnr
Linear coefficientscoef_lin
Obtain the linear coefficients of a Bayesian circular mixed-effects modelcoef_lin.bpnme
Obtain the linear coefficients of a Bayesian circular regression modelcoef_lin.bpnr
Random effect variancescoef_ran
Obtain random effect variances of a Bayesian circular mixed-effects modelcoef_ran.bpnme
Compute Model Fit Measures Regression ModelDIC_reg
Compute Eigenvalueseigen_val
Compute Eigenvectorseigen_vec
Model fitfit
Model fit for a Bayesian circular mixed-effects modelfit.bpnme
Model fit for a Bayesian circular regression modelfit.bpnr
Estimate the mode by finding the highest posterior density intervalhmode
Estimate the mode by finding the highest posterior density intervalhmodeC
Find the highest density interval.hmodeci
Find the highest density interval of a circular variablehmodeciC
Compute the 95 percent HPD of a vector of linear datahpd_est
Compute the 95 percent HPD of a vector of circular datahpd_est_circ
Compute the Likelihood of the PN distribution (mixed effects)lik_me
Compute the Likelihood of the PN distribution (regression)lik_reg
The geometry of human knowledge of navigation space.Maps
Compute the mean of a vector of circular datamean_circ
Create model matrices for a circular mixed-effects regression modelmmme
Create model matrices circular regressionmmr
Compute the mode of a vector of linear datamode_est
Compute the mode of a vector of circular datamode_est_circ
Phase differences in hand flexion-extension movements.Motor
Sample from a multivariate normal distributionmvrnorm_arma_eigen
A Gibbs sampler for a projected normal mixed-effects modelpnme
A Gibbs sampler for a projected normal regression modelpnr
Print output from a Bayesian circular mixed-effects modelprint.bpnme
Print output from a Bayesian circular regression modelprint.bpnr
Compute a mean resultant lengthrho
Compute the mean resultant length of a vector of circular datarho_circ
Compute the standard deviation of a vector of circular datasd_circ
A slice sampler for the latent lengths rslice_rcpp
Compute a mean directiontheta_bar
Traceplotstraceplot
Traceplots for a Bayesian circular mixed-effects modeltraceplot.bpnme
Traceplots for a Bayesian circular regression modeltraceplot.bpnr