R: Bayesian Projected Normal Regression Models for Circular Data

# Bayesian Projected Normal Regression Models for Circular Data

## Documentation for package ‘bpnreg’ version 2.0.3

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

BFc | Bayes Factors
BFc.bpnme | Bayes Factors for a Bayesian circular mixed-effects model
BFc.bpnr | Bayes Factors for a Bayesian circular regression model
bpnme | Fit a Bayesian circular mixed-effects model
bpnr | Fit a Bayesian circular regression model
circ_coef | Compute circular coefficients from linear coefficients
circ_coef_rcpp | Compute circular coefficients
coef_circ | Circular coefficients
coef_circ.bpnme | Obtain the circular coefficients of a Bayesian circular mixed-effects model
coef_circ.bpnr | Obtain the circular coefficients of a Bayesian circular regression model
coef_lin | Linear coefficients
coef_lin.bpnme | Obtain the linear coefficients of a Bayesian circular mixed-effects model
coef_lin.bpnr | Obtain the linear coefficients of a Bayesian circular regression model
coef_ran | Random effect variances
coef_ran.bpnme | Obtain random effect variances of a Bayesian circular mixed-effects model
DIC_reg | Compute Model Fit Measures Regression Model
eigen_val | Compute Eigenvalues
eigen_vec | Compute Eigenvectors
fit | Model fit
fit.bpnme | Model fit for a Bayesian circular mixed-effects model
fit.bpnr | Model fit for a Bayesian circular regression model
hmode | Estimate the mode by finding the highest posterior density interval
hmodeC | Estimate the mode by finding the highest posterior density interval
hmodeci | Find the highest density interval.
hmodeciC | Find the highest density interval of a circular variable
hpd_est | Compute the 95 percent HPD of a vector of linear data
hpd_est_circ | Compute the 95 percent HPD of a vector of circular data
lik_me | Compute the Likelihood of the PN distribution (mixed effects)
lik_reg | Compute the Likelihood of the PN distribution (regression)
Maps | The geometry of human knowledge of navigation space.
mean_circ | Compute the mean of a vector of circular data
mmme | Create model matrices for a circular mixed-effects regression model
mmr | Create model matrices circular regression
mode_est | Compute the mode of a vector of linear data
mode_est_circ | Compute the mode of a vector of circular data
Motor | Phase differences in hand flexion-extension movements.
mvrnorm_arma_eigen | Sample from a multivariate normal distribution
pnme | A Gibbs sampler for a projected normal mixed-effects model
pnr | A Gibbs sampler for a projected normal regression model
print.bpnme | Print output from a Bayesian circular mixed-effects model
print.bpnr | Print output from a Bayesian circular regression model
rho | Compute a mean resultant length
rho_circ | Compute the mean resultant length of a vector of circular data
sd_circ | Compute the standard deviation of a vector of circular data
slice_rcpp | A slice sampler for the latent lengths r
theta_bar | Compute a mean direction
traceplot | Traceplots
traceplot.bpnme | Traceplots for a Bayesian circular mixed-effects model
traceplot.bpnr | Traceplots for a Bayesian circular regression model