component
fun componentCountFrequency(data: DoubleArray, numBootstrapSamples: Int = defaultNumBootstrapSamples, numComponentsRange: IntRange = MixtureModeler.defaultNumComponentsRange, fitter: () -> ComponentFitterIfc = { PDFComponentFitter() }, criterion: MixtureCriterionIfc = MixtureBICCriterion(), refiner: () -> PartitionRefinerIfc = MixtureModeler.defaultRefiner, selector: () -> FamilySelectorIfc = MixtureModeler.defaultSelector, streamNum: Int = 0, streamProvider: RNStreamProviderIfc = KSLRandom.DefaultRNStreamProvider): MixtureBootstrapResults(source)
Refits the mixture on resamples of the data and tabulates what was recommended.
Parameters
data
the observations
num
how many resamples to draw
num
the numbers of components each refit considers
fitter
a factory for the component fitter; a fresh one per resample, since the fitter is wrapped in a cache keyed by group range and a cache carried across resamples would answer with another sample's fits
criterion
the criterion each refit ranks by
refiner
a factory for the refiner, fresh per resample for the same reason
selector
a factory for the family selector
stream
the stream to resample with
stream
the stream provider