KSLCore/ksl.utilities.distributions.fitting/PMFModeler

PMFModeler

class PMFModeler(data: IntArray) : PMFData(source)

Constructors

PMFModeler

constructor(data: IntArray)

Types

Companion

object Companion

Properties

data

open override val data: IntArray

Returns a copy of the integer data used to construct this modeler. A copy is returned so that the modeler's internal state cannot be modified by the caller.

defaultEstimators

val defaultEstimators: Set<ParameterEstimatorIfc>

This set holds the default set of estimators to try during the estimation process of the discrete distributions.

frequency

open override val frequency: IntegerFrequency

hasNegatives

open override val hasNegatives: Boolean

hasZeroes

open override val hasZeroes: Boolean

statistics

open override val statistics: StatisticIfc

Functions

estimateParameters

fun estimateParameters(estimators: Set<ParameterEstimatorIfc>): List<EstimationResult>

Estimates the parameters for all estimators represented by the set of estimators. Shifting of the data is not performed. It is assumed that the supplied estimators are appropriate for the supplied data.

toReport

fun PMFModeler.toReport(title: String = "Discrete Distribution Fitting — Data Analysis", confidenceLevel: Double = 0.95, block: ReportBuilder.() -> Unit = { discreteDataSummary(this@toReport, confidenceLevel = confidenceLevel) discreteVisualization(this@toReport) }): ReportNode.Document

Builds a ReportNode.Document containing a discrete data exploration report — statistical summary and visualization plots — with no goodness-of-fit analysis. Suitable for EDA before committing to a specific distribution.