A algorithm (#5)

* feat: a algorithm creeate result type

* feat: robust value added

* feat: add xiValues and robustDeviation calculation

* feat: add limit, high limit & low limit

* feat: create test outline

* feat: completed A algorithm ✅  (with fix test issues)

* style: format code style [BONUS ➕]

* style: add description variable

Author: burakodabas

src/algorithms/a-algorithm.ts

@@ -0,0 +1,26 @@
+import { median } from 'simple-statistics';
+import { AResult } from '../types';
+
+/**
+ * @param {number[]} values - an array of numbers
+ * @returns An object with the following properties:
+ * - robust =  x*
+ * - robustDeviation =  s*
+ * - highLimit
+ * - lowLimit
+ */
+export function A_Algorithm(values: number[]): AResult {
+  const robust = median(values); // robust value = median of the values
+  const xiValues = values.map((x) => Math.abs(x - robust)); // subtract the robust value from each value
+  const robustDeviation = median(xiValues) * 1.483;
+  const limit = robustDeviation * 1.5;
+  const highLimit = robust + limit;
+  const lowLimit = robust - limit;
+
+  return {
+    robust,
+    robustDeviation,
+    highLimit,
+    lowLimit,
+  };
+}

src/lib.ts

@@ -4,4 +4,6 @@ export * from './algorithms/made';
 
 export * from './algorithms/q-hampel';
 
+export * from './algorithms/a-algorithm';
+
 export * from './grubbs';

src/types.ts

@@ -2,3 +2,9 @@ export type Result = {
   value: number;
   uncertainty?: number;
 };
+export type AResult = {
+  robust: number;
+  robustDeviation: number;
+  highLimit: number;
+  lowLimit: number;  
+};

tests/algorithms.test.ts

@@ -1,6 +1,21 @@
-import { MADe, M_Estimator, Q, Hampel } from '../src/lib';
+import { MADe, M_Estimator, Q, Hampel, A_Algorithm } from '../src/lib';
 
 describe('Algorithms', () => {
+  it('A algorithm', () => {
+    const samples = [
+      0.04, 0.055, 0.178, 0.202, 0.206, 0.227, 0.228, 0.23, 0.23, 0.235, 0.236,
+      0.237, 0.243, 0.244, 0.245, 0.2555, 0.26, 0.264, 0.267, 0.27, 0.273,
+      0.274, 0.274, 0.278, 0.2811, 0.287, 0.287, 0.288, 0.289, 0.295, 0.296,
+      0.311, 0.331, 0.4246,
+    ];
+    const output = A_Algorithm(samples);
+
+    expect(output.robust).toBeCloseTo(0.262, 3);
+    expect(output.robustDeviation).toBeCloseTo(0.0386, 3);
+    expect(output.lowLimit).toBeCloseTo(0.2042, 3);
+    expect(output.highLimit).toBeCloseTo(0.3198, 3);
+  });
+
   it('MADe Method', () => {
     const samples = [13.9, 14.12, 13.65];
     const output = MADe(samples);