CovarianceResult

@Serializable

@SerialName(value = "CovarianceResult")

data class CovarianceResult(val totalWeights: Double, val meanX: Double, val meanY: Double, val sxy: Double, val sxx: Double, val syy: Double) : HasObservationCount(source)

Weighted covariance snapshot with second-moment sums usable for merging.

Constructors

constructor(totalWeights: Double, meanX: Double, meanY: Double, sxy: Double, sxx: Double, syy: Double)(source)

Pearson correlation coefficient.

Sample covariance sxy / totalWeights.

Weighted running mean of x.

Weighted running mean of y.

Sum of squared deviations in x: Sum (x - meanX)^2 * w.

Sum of cross-deviations: Sum (x - meanX)(y - meanY) * w.

Sum of squared deviations in y: Sum (y - meanY)^2 * w.

Cumulative observation weight folded in.

Population variance of x.

Population variance of y.

True when no observation has been folded in, so every other field is a placeholder.