evidence: Evidence ratio for model comparisons with AIC, AICc or BIC
In qpcR: Modelling and Analysis of Real-Time PCR Data

Description Usage Arguments Details Value Author(s) Examples

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.

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

`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`.

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.

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.

Andrej-Nikolai Spiess

## 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)

Loading required package: MASS
Loading required package: minpack.lm
Loading required package: rgl
Loading required package: robustbase
Loading required package: Matrix
Warning messages:
1: In rgl.init(initValue, onlyNULL) : RGL: unable to open X11 display
2: 'rgl_init' failed, running with rgl.useNULL = TRUE 
3: .onUnload failed in unloadNamespace() for 'rgl', details:
  call: fun(...)
  error: object 'rgl_quit' not found 
[1] 213.2002
[1] 0.2231302