BFc.bpnr: Bayes Factors for a Bayesian circular regression model

In joliencremers/bpnreg: Bayesian Projected Normal Regression Models for Circular Data

Bayes Factors for a Bayesian circular regression model

Description

Outputs Bayes Factors for the circular differences between several levels of a categorical variable and the baseline.

Usage

## S3 method for class 'bpnr'
BFc(object, hypothesis, type = "anchor")

Arguments

object	a bpnr object obtained from the function bpnr().
hypothesis	the inequality constrained hypothesis to test.
type	type of hypothesis to test c("anchor", "isotropic"). As of yet only anchor hypotheses can be tested.

Value

Bayes Factors for inequality constrained hypotheses on mean differences.

Examples

library(bpnreg)
fit.Motor <- bpnr(pred.I = Phaserad ~ 1 + Cond, data = Motor,
its = 100, burn = 10, n.lag = 3)
BFc(fit.Motor, hypothesis = "Condsemi.imp < Condimp")

joliencremers/bpnreg documentation built on Nov. 9, 2023, 4:55 a.m.