MDMA (version 1.1.0)

posteriorModelOdds: Posterior model odds

Description

Calculate the posterior model odds for a set of models.

Usage

posteriorModelOdds(...)

Value

posteriorModelOdds returns to posterior model odds for the models provided.

Arguments

...

objects of class (g)lm, given as separate arguments.

Author

Mathijs Deen

Details

Posterior model odds are calculated for every model \(i\) as $$\mathrm{pMO}_i = \frac{\mathrm{exp}\Big[-\frac{1}{2}\Delta_i\mathrm{BIC}\Big]}{\sum_{j = 1}^K\mathrm{exp}\Big[-\frac{1}{2}\Delta_j\mathrm{BIC}\Big]},$$ where the minimal BIC value is subtracted from all BICs. In other words: the model with the lowest BIC has \(\Delta\mathrm{BIC}=0\).

Examples

lm.1 <- lm(mpg ~ hp + wt, data = mtcars)
lm.2 <- lm(mpg ~ hp * wt, data = mtcars)
lm.3 <- lm(mpg ~ hp * wt + gear, data = mtcars)
posteriorModelOdds(lm.1, lm.2, lm.3)