posteriorModelOdds {MDMA}

Posterior model odds

Description

Calculate the posterior model odds for a set of models.

Usage

posteriorModelOdds(...)

Arguments

...

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

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.

Value

posteriorModelOdds returns to posterior model odds for the models provided.

Author(s)

Mathijs Deen

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)