KSLCore/ksl.app.dist.result/DistributionFitDTO

DistributionFitDTO

@Serializable

data class DistributionFitDTO(val rank: Int, val familyId: String, val estimatorId: String, val rvTypeName: String, val displayName: String, val parameters: Map<String, Double>, val numberOfParameters: Int, val success: Boolean, val message: String? = null, val shift: Double = 0.0, val weightedValue: Double? = null, val averageRanking: Double? = null, val firstRankCount: Int? = null, val chiSquaredPValue: Double? = null, val goodnessOfFit: GoodnessOfFitDTO? = null, val bootstrap: List<BootstrapEstimateDTO>? = null)(source)

Wire-safe, asymmetry-aware result for one (estimator, distribution-family) outcome. family + parameters + shift is everything a distribution-capable client needs to reconstruct the fitted distribution and build any fit-quality plot from its own raw data.

The continuous side populates the headline MODA fields (weightedValue, averageRanking, firstRankCount — the engine's OverallValueData); the full per-metric MODA breakdown lives once in the report's ModaResultDTO, joined by displayName == alternative. The discrete side populates chiSquaredPValue (a convenience mirror of goodnessOfFit?.chiSquaredPValue, used as the discrete ranking key).

goodnessOfFit and bootstrap are populated in a later phase by the result extractor; they are null until then.

Constructors

DistributionFitDTO

constructor(rank: Int, familyId: String, estimatorId: String, rvTypeName: String, displayName: String, parameters: Map<String, Double>, numberOfParameters: Int, success: Boolean, message: String? = null, shift: Double = 0.0, weightedValue: Double? = null, averageRanking: Double? = null, firstRankCount: Int? = null, chiSquaredPValue: Double? = null, goodnessOfFit: GoodnessOfFitDTO? = null, bootstrap: List<BootstrapEstimateDTO>? = null)