BFc.bpnme: Bayes Factors for a Bayesian circular mixed-effects model

In bpnreg: Bayesian Projected Normal Regression Models for Circular Data

Description

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

Usage

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

Arguments

object	a bpnme object obtained from the function bpnme.
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.Maps <- bpnme(pred.I = Error.rad ~ Maze + Trial.type + L.c + (1|Subject),
data = Maps, its = 100, burn = 1, n.lag = 1)
BFc(fit.Maps, hypothesis = "Maze1 < Trial.type1")

bpnreg documentation built on Aug. 6, 2021, 9:07 a.m.