kumulant/com.eignex.kumulant.stat.quantile/TDigestResult

TDigestResult

@Serializable

@SerialName(value = "TDigestResult")

data class TDigestResult(val probabilities: DoubleArray, val quantiles: DoubleArray, val means: DoubleArray, val weights: DoubleArray, val totalWeight: Double, val compression: Double) : Result(source)

T-digest snapshot: means/weights are the centroid arrays sorted by mean, with quantiles precomputed for probabilities via CDF inversion.

Constructors

TDigestResult

constructor(probabilities: DoubleArray, quantiles: DoubleArray, means: DoubleArray, weights: DoubleArray, totalWeight: Double, compression: Double)

Properties

compression

val compression: Double

T-digest compression parameter; lower = more centroids, tighter quantiles.

means

val means: DoubleArray

Centroid means sorted ascending; parallel to weights.

probabilities

val probabilities: DoubleArray

Probabilities at which quantiles are evaluated; parallel to quantiles.

quantiles

val quantiles: DoubleArray

Estimated quantile values, parallel to probabilities.

totalWeight

val totalWeight: Double

Cumulative observation weight folded in.

weights

val weights: DoubleArray

Centroid weights, parallel to means.

Functions

toSparseHistogram

fun TDigestResult.toSparseHistogram(): SparseHistogramResult

Convert centroids to a sparse histogram with bins centered on each centroid.

TDigestResult

constructor(probabilities: DoubleArray, quantiles: DoubleArray, means: DoubleArray, weights: DoubleArray, totalWeight: Double, compression: Double)(source)

compression

val compression: Double(source)

T-digest compression parameter; lower = more centroids, tighter quantiles.

means

val means: DoubleArray(source)

Centroid means sorted ascending; parallel to weights.

probabilities

val probabilities: DoubleArray(source)

Probabilities at which quantiles are evaluated; parallel to quantiles.

quantiles

val quantiles: DoubleArray(source)

Estimated quantile values, parallel to probabilities.

totalWeight

val totalWeight: Double(source)

Cumulative observation weight folded in.

weights

val weights: DoubleArray(source)

Centroid weights, parallel to means.