"use strict";
|
/**
|
* @license
|
* Copyright 2018 Google Inc. All Rights Reserved.
|
* Licensed under the Apache License, Version 2.0 (the "License");
|
* you may not use this file except in compliance with the License.
|
* You may obtain a copy of the License at
|
*
|
* http://www.apache.org/licenses/LICENSE-2.0
|
*
|
* Unless required by applicable law or agreed to in writing, software
|
* distributed under the License is distributed on an "AS IS" BASIS,
|
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
* See the License for the specific language governing permissions and
|
* limitations under the License.
|
* =============================================================================
|
*/
|
Object.defineProperty(exports, "__esModule", { value: true });
|
var test_util_1 = require("../test_util");
|
function jarqueBeraNormalityTest(values) {
|
// https://en.wikipedia.org/wiki/Jarque%E2%80%93Bera_test
|
var n = values.length;
|
var s = skewness(values);
|
var k = kurtosis(values);
|
var jb = n / 6 * (Math.pow(s, 2) + 0.25 * Math.pow(k - 3, 2));
|
// JB test requires 2-degress of freedom from Chi-Square @ 0.95:
|
// http://www.itl.nist.gov/div898/handbook/eda/section3/eda3674.htm
|
var CHI_SQUARE_2DEG = 5.991;
|
if (jb > CHI_SQUARE_2DEG) {
|
throw new Error("Invalid p-value for JB: " + jb);
|
}
|
}
|
exports.jarqueBeraNormalityTest = jarqueBeraNormalityTest;
|
function expectArrayInMeanStdRange(actual, expectedMean, expectedStdDev, epsilon) {
|
if (epsilon == null) {
|
epsilon = test_util_1.testEpsilon();
|
}
|
var actualMean = mean(actual);
|
test_util_1.expectNumbersClose(actualMean, expectedMean, epsilon);
|
test_util_1.expectNumbersClose(standardDeviation(actual, actualMean), expectedStdDev, epsilon);
|
}
|
exports.expectArrayInMeanStdRange = expectArrayInMeanStdRange;
|
function mean(values) {
|
var sum = 0;
|
for (var i = 0; i < values.length; i++) {
|
sum += values[i];
|
}
|
return sum / values.length;
|
}
|
function standardDeviation(values, mean) {
|
var squareDiffSum = 0;
|
for (var i = 0; i < values.length; i++) {
|
var diff = values[i] - mean;
|
squareDiffSum += diff * diff;
|
}
|
return Math.sqrt(squareDiffSum / values.length);
|
}
|
function kurtosis(values) {
|
// https://en.wikipedia.org/wiki/Kurtosis
|
var valuesMean = mean(values);
|
var n = values.length;
|
var sum2 = 0;
|
var sum4 = 0;
|
for (var i = 0; i < n; i++) {
|
var v = values[i] - valuesMean;
|
sum2 += Math.pow(v, 2);
|
sum4 += Math.pow(v, 4);
|
}
|
return (1 / n) * sum4 / Math.pow((1 / n) * sum2, 2);
|
}
|
function skewness(values) {
|
// https://en.wikipedia.org/wiki/Skewness
|
var valuesMean = mean(values);
|
var n = values.length;
|
var sum2 = 0;
|
var sum3 = 0;
|
for (var i = 0; i < n; i++) {
|
var v = values[i] - valuesMean;
|
sum2 += Math.pow(v, 2);
|
sum3 += Math.pow(v, 3);
|
}
|
return (1 / n) * sum3 / Math.pow((1 / (n - 1)) * sum2, 3 / 2);
|
}
|
//# sourceMappingURL=rand_util.js.map
|