DIC_reg

output from the circular regression function Regression()

Output

model matrix for the first component

model matrix for the second component

Compute Model Fit Measures Regression Model

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 Nu<c3><b1>ez-Antonio & Gutti<c3><a9>rez-Pe<c3><b1>a (2014)
<doi:10.1016/j.csda.2012.07.025>.

DIC_reg: Compute Model Fit Measures Regression Model

Description

Usage

Arguments