mchoice {qpcR} | R Documentation |
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.
mchoice(object, sig.level = 0.05, verbose = TRUE)
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. |
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.
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.
Andrej-Nikolai Spiess & Christian Ritz
m1 <- multdrc(F1.1 ~ Cycles, data = reps, fct = l3()) ### choose best model m2 <- mchoice(m1) summary(m2) ### Converted to l5() model ! plot(m2, log = "")