covariance
fun covariance(x: DoubleArray, y: DoubleArray, kind: PopulationKind = PopulationKind.SAMPLE): Double(source)
Computes the covariance between two arrays.
Covariance measures how two variables change together. A positive value means they tend to increase together, a negative value means one tends to increase when the other decreases, and a value near zero means no linear association. Unlike correlation, the magnitude of covariance depends on the scale of the variables.
Example:
val x = doubleArrayOf(1.0, 2.0, 3.0, 4.0, 5.0)
val y = doubleArrayOf(2.0, 4.0, 6.0, 8.0, 10.0)
covariance(x, y) // 5.0 (sample covariance)Content copied to clipboard
Return
Parameters
x
the first array of observations.
y
the second array of observations, must have the same size as x.
kind
whether to compute sample or population covariance. Defaults to PopulationKind.SAMPLE, which divides by n-1 (Bessel's correction) to produce an unbiased estimate.
Throws
if there are fewer than 2 observations.