Provides a convenient way to compare different kinetic models fitted to the same dataset.

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

# S3 method for mmkin
BIC(object, ...)

Arguments

object

An object of class mmkin, containing only one column.

...

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).

Examples

# 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)
#> Warning: Optimisation did not converge: #> false convergence (8)
AIC(f[1, "FOCUS A"]) # We get a single number for a single fit
#> [1] 55.28197
# 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"])
#> df AIC #> SFO 3 55.28197 #> FOMC 4 57.28202 #> DFOP 5 59.28197
AIC(f[, "FOCUS A"], k = 0) # If we do not penalize additional parameters, we get nearly the same
#> df AIC #> SFO 3 49.28197 #> FOMC 4 49.28202 #> DFOP 5 49.28197
# For FOCUS C, the more complex models fit better AIC(f[, "FOCUS C"])
#> df AIC #> SFO 3 59.29336 #> FOMC 4 44.68652 #> DFOP 5 29.02372