mselect {drc} | R Documentation |
Model selection by comparison of different models using 1) the maximum log likelihood value, 2) Akaike's information criteria (AIC), 3) the estimated residual variance and 4) the p-value from a lack-of-fit test as criteria.
mselect(object, fctList = NULL, nested = FALSE)
object |
an object of class 'drc'. |
fctList |
a list of non-linear functions to be compared. |
nested |
logical. TRUE results in F tests between adjacent (in 'fctList') models. Only sensible for nested models. |
Criterion 1) cannot be used for comparison unless the models are nested ().
For criteria 2) and 3): the smaller the better; for criterion 4) the larger the better.
A matrix with one row for each model and one column for each criterion.
Christian Ritz
## Fitting initial model m1 <- multdrc(ryegrass) ## Model selection mselect(m1, list(l3(), l5(), W1.3(), W1.4(), weibull2(), baro5(), richards())) mselect(m1, list(l5())) # nested models