bayes_R2: Computes R-squared using Bayesian R-squared approach.

In bistablehistory: Cumulative History Analysis for Bistable Perception Time Series

Computes R-squared using Bayesian R-squared approach.

Description

For detail refer to: Andrew Gelman, Ben Goodrich, Jonah Gabry, and Aki Vehtari (2018). R-squared for Bayesian regression models. The American Statistician \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1080/00031305.2018.1549100")} and https://avehtari.github.io/bayes_R2/bayes_R2.html

Usage

## S3 method for class 'cumhist'
bayes_R2(object, summary = TRUE, probs = c(0.055, 0.945), ...)

Arguments

object	An object of class cumhist
summary	Whether summary statistics should be returned instead of raw sample values. Defaults to TRUE
probs	The percentiles used to compute summary, defaults to 89% credible interval.
...	Unused.

Value

vector of values or a data.frame with summary

Examples

br_fit <- fit_cumhist(br_singleblock, state = "State", duration = "Duration")
bayes_R2(br_fit)

bistablehistory documentation built on Sept. 13, 2023, 5:07 p.m.