#5 - Root mean square

README.md

@@ -21,6 +21,7 @@ npm i stat-methods
     -   [mean](#mean)
     -   [harmonicMean](#harmonicMean)
     -   [geometricMean](#geometricMean)
+    -   [rootMeanSquare](#rootMeanSquare)
     -   [median](#median)
     -   [medianLow](#medianLow)
     -   [medianHigh](#medianHigh)
@@ -52,6 +53,7 @@ These methods compute an average or typical value from a population or sample.
 -   [mean](#mean): Arithmetic mean ('average')
 -   [harmonicMean](#harmonicMean): Harmonic mean ('subcontrary mean')
 -   [geometricMean](#geometricMean): Geometric mean
+-   [rootMeanSquare](#rootMeanSquare): Root mean square
 -   [median](#median): Median (middle value)
 -   [medianLow](#medianLow): Low median
 -   [medianHigh](#medianHigh): High median
@@ -135,6 +137,22 @@ geometricMean([1, -2, 3, 4]); // -> undefined
 
 If the data array is empty or contains a non finite `Number`, the method returns `undefined`.
 
+#### rootMeanSquare
+
+```js
+rootMeanSquare(arr);
+```
+
+Return the root mean square of a numeric data array `arr`.
+
+The root mean square is the square root of the mean square (the arithmetic mean of the squares of a set of numbers).
+
+```js
+rootMeanSquare([4, 1, 1/32]); // -> 2.380544514916703
+```
+
+If the data array is empty or contains a non finite `Number`, the method returns `undefined`.
+
 #### median
 
 ```js

src/central.js

@@ -58,6 +58,22 @@ export function geometricMean(arr) {
   return nthRoot(prod, arr.length);
 }
 
+/**
+ * Return the root mean square of a numeric data array.
+ * The root mean square is the square root of the
+ * mean square (the arithmetic mean of the squares of a set of numbers).
+ * @param {Number[]} arr the data array
+ * @returns {Number} the arithmetic mean of the data array
+ */
+export function rootMeanSquare(arr) {
+  if (min(arr) === undefined) return undefined;
+  let arrSquareSum = 0;
+  for (let i = 0; i < arr.length; i += 1) {
+    arrSquareSum += arr[i] ** 2;
+  }
+  return Math.sqrt((arrSquareSum / arr.length));
+}
+
 /**
  * Return the median (middle value) of a numeric data array.
  * The median is the value separating the higher half from the lower half of a data sample.

test/central.test.js

@@ -3,6 +3,7 @@ import {
   mean,
   harmonicMean,
   geometricMean,
+  rootMeanSquare,
   median,
   medianLow,
   medianHigh,
@@ -52,6 +53,22 @@ describe('Averages and measures of central location', () => {
     testUndefinedWithNullable(geometricMean);
   });
 
+  test('Root mean square', () => {
+    expect(rootMeanSquare([4, 1, 1, 3])).toBe(2.598076211353316);
+    expect(rootMeanSquare([1, 2, 4])).toBe(2.6457513110645907);
+    expect(rootMeanSquare([4, 1, 1/32])).toBe(2.380544514916703);
+    expect(rootMeanSquare([1.1, 1.4, 3.5, 9.5])).toBe(5.139795715784821);
+    expect(rootMeanSquare([2.5, 0, 10])).toBe(5.951190357119041);
+    expect(rootMeanSquare([-1, 2, 4])).toBe(2.6457513110645907);
+    expect(rootMeanSquare([-1, 2, 4, 2])).toBe(2.5);
+    expect(rootMeanSquare(['a', 2.5, 'b', 5.75])).toBeUndefined();
+    expect(rootMeanSquare([NaN, 2.5, 3, 5.75])).toBeUndefined();
+    expect(rootMeanSquare([])).toBeUndefined();
+    expect(rootMeanSquare(3)).toBeUndefined();
+    expect(rootMeanSquare([3])).toBe(3);
+    testUndefinedWithNullable(rootMeanSquare);
+  });
+
   test('Median', () => {
     expect(median([1, 12, 3, 15, 6, 8, 9])).toBe(8);
     expect(median([1, -2, 3, 4, 8, 6, 5, 9])).toBe(4.5);