Mean Absolute Deviation
Install and import#
npm install fintech-algorithmsimport { meanAbsoluteDeviation } from "fintech-algorithms/foundations/dispersion-shape-and-robust-statistics/mean-absolute-deviation";Signature#
meanAbsoluteDeviation(input)Averages the absolute distances of the observations from their arithmetic mean, giving a spread figure in the same units as the data and without squaring.
Parameters#
| Name | Type | Notes |
|---|---|---|
input | { values: number[] } | The observations to measure, under the key values. The centre used is the arithmetic mean of this same series, not a supplied reference point. |
Returns#
{ meanAbsoluteDeviation: number; center: number }
meanAbsoluteDeviation is the average absolute distance from the centre, and center is the arithmetic mean the distances were taken from.
Errors#
- When
inputis null, an array, or not an object — throws TypeError - When
valuesis missing, is not an array, or is empty — throws RangeError - When any entry of
valuesdoes not coerce to a finite number — throws RangeError
Complexity: time O(n log n),
space O(n).
Worked example#
verified This is the worked example published in the article, replayed by the test suite on every run. The output cannot drift.
Input#
{
"values": [1, 2, 2, 4, 9]
}Call#
meanAbsoluteDeviation(input)Returns#
object with 2 fields: meanAbsoluteDeviation, center
{
"meanAbsoluteDeviation": 2.3200000000000003,
"center": 3.6
}Diagrams#
How it works#
This page states the contract — how to call it correctly. The article explains the concept: why it works, and where it breaks.
References#
- Measures of Scale — NIST/SEMATECH e-Handbook
- Skewness and Kurtosis — NIST/SEMATECH e-Handbook
- Historical-example decision