KSLCore/ksl.utilities.distributions.fitting.scoring/QQSSEScoringModel

QQSSEScoringModel

class QQSSEScoringModel(var empDistType: EmpDistType = EmpDistType.Continuity1) : PDFScoringModel

This scoring model represents the sum of squared errors of a Q-Q plot for a fitted distribution. The sum of squared difference between the empirical quantiles and the order statistics for the data set is computed and returned as the score.

Constructors

QQSSEScoringModel

constructor(empDistType: EmpDistType = EmpDistType.Continuity1)

Properties

allowLowerLimitAdjustment

open override val allowLowerLimitAdjustment: Boolean = true

Indicates if the lower limit of the domain may be adjusted during scaling processes

allowUpperLimitAdjustment

open override val allowUpperLimitAdjustment: Boolean = true

Indicates if the upper limit of the domain may be adjusted during scaling processes

description

open override var description: String?

direction

open override var direction: MetricIfc.Direction

domain

override val domain: Interval

empDistType

var empDistType: EmpDistType

name

open override val name: String

unitsOfMeasure

open override var unitsOfMeasure: String?

Functions

badScore

open fun badScore(): Score

Returns a valid score that has the worst possible value according to the direction of the meaning of better.

metricData

open fun metricData(modaName: String, weight: Double): MetricData

Returns an instance of MetricData based on (modaName, weight)

newInstance

open override fun newInstance(): QQSSEScoringModel

score

fun score(result: EstimationResult): Score

fun score(data: DoubleArray, parameters: RVParameters): Score

open override fun score(data: DoubleArray, cdf: ContinuousDistributionIfc): Score

toString

open override fun toString(): String