compareAIC: Calculates the probability of each model from a set of...

Description Usage Arguments Value See Also Examples

View source: R/compareaic.R

Description

For a given set of AIC from models, the probability of each model relative to the rest of the models of the set is calculated using the following formula:

Usage

1

Arguments

...

a list with the model metrics, the output from modelTurnover and calculateAIC.

Value

a list with a matrix for each experiment condition. The matrix contains the probabilities of each model (columns) for each protein/peptide (rows).

See Also

calculateAIC, modelTurnover.

Examples

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

modelList1 <- modelTurnover(x = wormsPE[1:10],
                           assayName = 'fraction',
                           formula = 'fraction ~ 1 - exp(-k*t)',
                           start = list(k = 0.02),
                           mode = 'protein',
                           robust = FALSE,
                           returnModel = TRUE)

modelList1 <- calculateAIC(modelList1, smallSampleSize = TRUE)

modelList2 <- modelTurnover(x = wormsPE[1:10],
                           assayName = 'fraction',
                           formula = 'fraction ~ 1 - exp(-k*t) + b',
                           start = list(k = 0.02, b = 0),
                           mode = 'protein',
                           robust = FALSE,
                           returnModel = TRUE)

modelList2 <- calculateAIC(modelList2, smallSampleSize = TRUE)

modelProbabilities <- compareAIC(modelList1, modelList2)

marcpaga/pulsedSilac documentation built on March 11, 2020, 8:49 p.m.