Discrete
open class DiscretePMFGoodnessOfFit(data: DoubleArray, val distribution: DiscretePMFInRangeDistributionIfc, numEstimatedParameters: Int = 1, breakPoints: DoubleArray = PMFModeler.makeZeroToInfinityBreakPoints(data.size, distribution)) : DistributionGOF, DiscreteDistributionGOFIfc(source)
Inheritors
Constructors
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constructor(data: DoubleArray, distribution: DiscretePMFInRangeDistributionIfc, numEstimatedParameters: Int = 1, breakPoints: DoubleArray = PMFModeler.makeZeroToInfinityBreakPoints(data.size, distribution))
Functions
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fun DiscretePMFGoodnessOfFit.toReport(modeler: PMFModeler, title: String = "Discrete Distribution Fitting Analysis", confidenceLevel: Double = 0.95, block: ReportBuilder.() -> Unit = {
discreteDataSummary(modeler, confidenceLevel = confidenceLevel)
discreteVisualization(modeler)
discreteGoodnessOfFit(this@toReport, modeler, confidenceLevel = confidenceLevel)
}): ReportNode.Document
Builds a ReportNode.Document containing a full discrete distribution fitting report: data statistical summary, visualization plots, and chi-squared goodness-of-fit analysis with a PMF comparison plot.