qpcR (version 1.1-3)

mchoice: Selection of the best model by nested F-tests

Description

Model selection by comparison of different models using 1) the maximum log likelihood value, 2) Akaike's Information Criterion, 3) bias-corrected Akaike's Information Criterion, 4) the estimated residual variance and 5) the p-value from a nested F-test on the residual variance. The best model is chosen by 5) and returned as a new model.

Usage

mchoice(object, sig.level = 0.05, verbose = TRUE)

Arguments

object

an object of class 'drc'.

sig.level

the significance level for the nested F-test.

verbose

logical. If TRUE, the result matrix is displayed in the console.

Value

• A 'drc' model of the best fit selected by the nested F-tests. The new model has an additional list item 'retMat' with the result matrix from the criterion tests.

Details

Criterion 5) cannot be used for comparison unless the models are nested. For criterion 1) the larger the better. For criteria 2), 3) and 4): the smaller the better. The best model is chosen from the nested F-test and returned as a new 'drc' model.

Examples

m1 <- multdrc(F1.1 ~ Cycles, data = reps, fct = l3())
### choose best model
m2 <- mchoice(m1)
summary(m2)  ### Converted to l5() model !
plot(m2, log = "")