evidence {qpcR}

Evidence ratio for model comparisons with AIC, AICc or BIC

Description

The evidence ratio

\frac{1}{exp(-0.5 \cdot (IC2 - IC1))}

is calculated for one of the information criteria IC = AIC, AICc, BIC either from two fitted models or two numerical values. Models can be compared that are not nested and where the f-test on residual-sum-of-squares is not applicable.

Usage

evidence(x, y, type = c("AIC", "AICc", "BIC"))

Arguments

x

a fitted object or numerical value.

y

a fitted object or numerical value.

type

any of the three Information Criteria AIC, AICc or BIC.

Details

Small differences in values can mean substantial more 'likelihood' of one model over the other. For example, a model with AIC = -130 is nearly 150 times more likely than a model with AIC = -120.

Value

A value of the first model x being more likely than the second model y. If large, first model is better. If small, second model is better.

Author(s)

Andrej-Nikolai Spiess

Examples

## Compare two four-parameter and five-parameter
## log-logistic models.
m1 <- pcrfit(reps, 1, 2, l4)
m2 <- pcrfit(reps, 1, 2, l5)
evidence(m2, m1)

## Ratio of two AIC's.
evidence(-120, -123)