AIC.mmkin {mkin} | R Documentation |
Provides a convenient way to compare different kinetic models fitted to the same dataset.
## S3 method for class 'mmkin' AIC(object, ..., k = 2) ## S3 method for class 'mmkin' BIC(object, ...)
object |
An object of class |
... |
For compatibility with the generic method |
k |
As in the generic method |
As in the generic method (a numeric value for single fits, or a dataframe if there are several fits in the column).
Johannes Ranke
## 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)