AIC.mmkin {mkin} | R Documentation |
Calculate the AIC for a column of an mmkin object
Description
Provides a convenient way to compare different kinetic models fitted to the same dataset.
Usage
## S3 method for class 'mmkin'
AIC(object, ..., k = 2)
## S3 method for class 'mmkin'
BIC(object, ...)
Arguments
object |
An object of class |
... |
For compatibility with the generic method |
k |
As in the generic method |
Value
As in the generic method (a numeric value for single fits, or a dataframe if there are several fits in the column).
Author(s)
Johannes Ranke
Examples
## Not run: # skip, as it takes > 10 s on winbuilder
f <- mmkin(c("SFO", "FOMC", "DFOP"),
list("FOCUS A" = FOCUS_2006_A,
"FOCUS C" = FOCUS_2006_C), cores = 1, quiet = TRUE)
# We get a warning because the FOMC model does not converge for the
# FOCUS A dataset, as it is well described by SFO
AIC(f["SFO", "FOCUS A"]) # We get a single number for a single fit
AIC(f[["SFO", "FOCUS A"]]) # or when extracting an mkinfit object
# For FOCUS A, the models fit almost equally well, so the higher the number
# of parameters, the higher (worse) the AIC
AIC(f[, "FOCUS A"])
AIC(f[, "FOCUS A"], k = 0) # If we do not penalize additional parameters, we get nearly the same
BIC(f[, "FOCUS A"]) # Comparing the BIC gives a very similar picture
# For FOCUS C, the more complex models fit better
AIC(f[, "FOCUS C"])
BIC(f[, "FOCUS C"])
## End(Not run)
[Package mkin version 1.2.6 Index]