calculateAIC: Calculates the Akaike Information Criteria (AIC)
In pulsedSilac: Analysis of pulsed-SILAC quantitative proteomics data

Description Usage Arguments Details Value See Also Examples

Calculates the AIC for each of the computed models. Requires that modelTurnover is run with reuturnModel = TRUE.

1	calculateAIC(modelList, smallSampleSize = TRUE)

`modelList`	a `list` with the model metrics, the output from `modelTurnover`.
`smallSampleSize`	a `logical` indicating if the AIC small sample size correction formula should be used.

The following formulas are used to compute the AIC and AICc (small sample size correction):

$AIC = 2k - 2ln(logLik)$ $AICc = AIC + \frac{2k(k + 1)}{n - k - 1}$

a list with the model metrics (the given input) plus a matrix named "AIC" with the AIC for each value

compareAIC, modelTurnover

data('wormsPE')
wormsPE <- calculateIsotopeFraction(wormsPE, ratioAssay = 'ratio')

modelList <- modelTurnover(x = wormsPE[1:10],
                           assayName = 'fraction',
                           formula = 'fraction ~ 1 - exp(-k*t)',
                           start = list(k = 0.02),
                           mode = 'protein',
                           robust = FALSE,
                           returnModel = TRUE)

modelList <- calculateAIC(modelList, smallSampleSize = TRUE)