README.md

In mcbeem/visualizeBF: Function for Visualizing the Bayes Factor for the Mean of Continuous Data

The visualizeBF package is useful for teaching about Bayes Factors, providing two different visual interpretations of the concept.

This is mostly a toy package useful for teaching.

Installation

You need the devtools package to install this from github.

install.packages("devtools")

Then install visualizeBF.

devtools::install_github("mcbeem/visualizeBF")

And then load it.

library(visualizeBF)

Example

First, simulate some data.

set.seed(1)
data <- rnorm(n=50, mean=.3, sd=1)

Visualize the BF as the ratio of the weighted average likelihood under H1 to the likelihood of the data under H0 (via plot=1).

visualizeBF(data, plot=1)

## $figure
## 
## $L.m0
## [1] 7.698952e-34
## 
## $L.m1
## [1] 3.266346e-32
## 
## $prior.mu0
## [1] 0.5280117
## 
## $posterior.mu0
## [1] 0.01244552
## 
## $BF10
## [1] 42.42585
## 
## $BF01
## [1] 0.02357053
## 
## $note
## [1] "Run dev.off() at the console to restore plot defaults."

Visualize the BF as the ratio of prior to posterior density under H0 (via plot=2).

visualizeBF(data, plot=2)

## $figure
## 
## $L.m0
## [1] 7.698952e-34
## 
## $L.m1
## [1] 3.266346e-32
## 
## $prior.mu0
## [1] 0.5280117
## 
## $posterior.mu0
## [1] 0.01244552
## 
## $BF10
## [1] 42.42585
## 
## $BF01
## [1] 0.02357053
## 
## $note
## [1] "Run dev.off() at the console to restore plot defaults."

mcbeem/visualizeBF documentation built on Nov. 19, 2019, 12:35 a.m.