centralMoment
Computes the n-th central moment of the values.
The r-th central moment is the average of the r-th power of deviations from the mean, dividing by n (population-style). Order 0 returns 1.0 by convention, order 1 returns 0.0 by definition, and order 2 equals the population variance. Odd central moments measure asymmetry, while even central moments measure tail weight.
Uses a two-pass algorithm with z-normalization (dividing deviations by the standard deviation) to prevent overflow with large-magnitude data.
Example:
listOf(2.0, 4.0, 4.0, 4.0, 5.0, 5.0, 7.0, 9.0).centralMoment(2) // 4.0
listOf(2.0, 4.0, 4.0, 4.0, 5.0, 5.0, 7.0, 9.0).centralMoment(3) // 5.25Return
the central moment of the given order.
Parameters
the moment order. Must be non-negative.
See also
Computes the n-th central moment of the values.
The r-th central moment is the average of the r-th power of deviations from the mean, dividing by n (population-style). Order 0 returns 1.0 by convention, order 1 returns 0.0 by definition, and order 2 equals the population variance. Odd central moments measure asymmetry, while even central moments measure tail weight.
Uses a two-pass algorithm with z-normalization (dividing deviations by the standard deviation) to prevent overflow with large-magnitude data.
Example:
doubleArrayOf(2.0, 4.0, 4.0, 4.0, 5.0, 5.0, 7.0, 9.0).centralMoment(2) // 4.0
doubleArrayOf(2.0, 4.0, 4.0, 4.0, 5.0, 5.0, 7.0, 9.0).centralMoment(3) // 5.25Return
the central moment of the given order.
Parameters
the moment order. Must be non-negative.
See also
Computes the n-th central moment of the values in this sequence.
The r-th central moment is the average of the r-th power of deviations from the mean, dividing by n (population-style). Order 0 returns 1.0 by convention, order 1 returns 0.0 by definition, and order 2 equals the population variance. Odd central moments measure asymmetry, while even central moments measure tail weight.
Uses a two-pass algorithm with z-normalization (dividing deviations by the standard deviation) to prevent overflow with large-magnitude data. The sequence is materialized into a list internally.
Example:
sequenceOf(2.0, 4.0, 4.0, 4.0, 5.0, 5.0, 7.0, 9.0).centralMoment(2) // 4.0
sequenceOf(2.0, 4.0, 4.0, 4.0, 5.0, 5.0, 7.0, 9.0).centralMoment(3) // 5.25Return
the central moment of the given order.
Parameters
the moment order. Must be non-negative.