qpcR (version 1.4-2)

evidence: 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"))

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.

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.

Author

Andrej-Nikolai Spiess

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.

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)