chi-sq-test/goodness-of-fit-test.js

Chi-Squared hypothesis tests to test distribution fitness for dataset and independence among datasets

"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.goodnessOfFit = void 0;
var chi_squared_1 = require("chi-squared");
var utils_1 = require("./utils");
var goodnessOfFit = function (observed, expected, ddof) {
    if (ddof === void 0) { ddof = 0; }
    if (!(observed === null || observed === void 0 ? void 0 : observed.length)) {
        (0, utils_1.throwError)('expected frequency must be an array of size > 0');
    }
    if (!expected && (observed === null || observed === void 0 ? void 0 : observed.length) > 0) {
        expected = Array.apply(null, Array(observed.length)).map(Number.prototype.valueOf, 0);
        // expected = new Array(observed.length).fill(observed.reduce(reducer) / observed.length);
    }
    else if ((expected === null || expected === void 0 ? void 0 : expected.length) !== observed.length) {
        (0, utils_1.throwError)('Observed and expected frequency arrays must be of same length');
    }
    // @ts-ignore
    var chisq = observed.reduce(function (a, c, i) { return a + ((Math.pow((c - expected[i]), 2)) / expected[i]); }, 0);
    return {
        value: chisq,
        pValue: 1 - (0, chi_squared_1.cdf)(chisq, observed.length - 1 - ddof),
    };
};
exports.goodnessOfFit = goodnessOfFit;