BayesianInfoCriterionScoringModel

class BayesianInfoCriterionScoringModel(val domain: Interval = DEFAULT_BIG_RANGE) : PDFScoringModel

Computes the Bayesian Information Criterion (BIC) based on the data as the score. This assumes that the parameters of the supplied distribution have been estimated from the data and evaluates the likelihood associated with the current parameters of the distribution. The parameters of the distribution are not assumed to have been estimated from a maximum likelihood approach.

Constructors

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constructor(domain: Interval = DEFAULT_BIG_RANGE)

Properties

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open override val allowLowerLimitAdjustment: Boolean = true

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

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open override val allowUpperLimitAdjustment: Boolean = true

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

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open override var description: String?
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open override var direction: MetricIfc.Direction
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override val domain: Interval
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open override val name: String
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open override var unitsOfMeasure: String?

Functions

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open fun badScore(): Score

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

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

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

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open override fun score(data: DoubleArray, cdf: ContinuousDistributionIfc): Score
fun score(data: DoubleArray, parameters: RVParameters): Score
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open override fun toString(): String