mkin (version 1.2.6)

AIC.mmkin: 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 mmkin
AIC(object, ..., k = 2)
# S3 method for mmkin
BIC(object, ...)

Value

As in the generic method (a numeric value for single fits, or a dataframe if there are several fits in the column).

Arguments

object

An object of class mmkin, containing only one column.

...

For compatibility with the generic method

k

As in the generic method

Author

Johannes Ranke

Examples

  if (FALSE)  # 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"])