205 lines
5.5 KiB
JavaScript
205 lines
5.5 KiB
JavaScript
/**
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* @license Apache-2.0
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*
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* Copyright (c) 2018 The Stdlib Authors.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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'use strict';
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// MODULES //
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var isCollection = require( '@stdlib/assert/is-collection' );
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var isPlainObject = require( '@stdlib/assert/is-plain-object' );
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var setReadOnly = require( '@stdlib/utils/define-read-only-property' );
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var objectKeys = require( '@stdlib/utils/keys' );
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var qnorm = require( './../../base/dists/normal/quantile' );
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var chisqCDF = require( './../../base/dists/chisquare/cdf' );
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var group = require( '@stdlib/utils/group' );
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var ranks = require( './../../ranks' );
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var abs = require( '@stdlib/math/base/special/abs' );
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var pow = require( '@stdlib/math/base/special/pow' );
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var indexOf = require( '@stdlib/utils/index-of' );
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var median = require( './median.js' );
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var validate = require( './validate.js' );
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var print = require( './print.js' ); // eslint-disable-line stdlib/no-redeclare
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// FUNCTIONS //
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/**
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* Returns an array of a chosen length filled with the supplied value.
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*
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* @private
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* @param {*} val - value to repeat
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* @param {NonNegativeInteger} len - array length
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* @returns {Array} filled array
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*/
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function repeat( val, len ) {
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var out = new Array( len );
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var i;
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for ( i = 0; i < len; i++ ) {
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out[ i ] = val;
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}
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return out;
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}
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// MAIN //
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/**
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* Computes the Fligner-Killeen test for equal variances.
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*
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* @param {...NumericArray} arguments - either two or more number arrays or a single numeric array if an array of group indicators is supplied as an option
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* @param {Options} [options] - function options
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* @param {number} [options.alpha=0.05] - significance level
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* @param {Array} [options.groups] - array of group indicators
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* @throws {TypeError} must provide array-like arguments
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* @throws {RangeError} alpha option has to be a number in the interval `[0,1]`
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* @throws {Error} must provide at least two array-like arguments if `groups` is not set
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* @throws {TypeError} options has to be simple object
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* @throws {TypeError} must provide valid options
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* @returns {Object} test results
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*
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* @example
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* // Data from Hollander & Wolfe (1973), p. 116:
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* var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];
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* var y = [ 3.8, 2.7, 4.0, 2.4 ];
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* var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];
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*
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* var out = fligner( x, y, z );
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* // returns {...}
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*/
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function fligner() {
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var variance;
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var options;
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var ngroups;
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var levels;
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var groups;
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var scores;
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var table;
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var alpha;
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var delta;
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var args;
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var mean;
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var opts;
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var pval;
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var sums;
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var xabs;
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var stat;
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var err;
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var loc;
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var out;
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var df;
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var M2;
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var a;
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var n;
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var x;
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var i;
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var j;
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args = [];
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ngroups = arguments.length;
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opts = {};
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if ( isPlainObject( arguments[ ngroups - 1 ] ) ) {
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options = arguments[ ngroups - 1 ];
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ngroups -= 1;
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err = validate( opts, options );
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if ( err ) {
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throw err;
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}
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}
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if ( opts.groups ) {
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groups = opts.groups;
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table = group( arguments[ 0 ], groups );
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levels = objectKeys( table );
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ngroups = levels.length;
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if ( ngroups < 2 ) {
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throw new Error( 'invalid number of groups. `groups` array must contain at least two unique elements. Value: `' + levels + '`.' );
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}
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for ( i = 0; i < ngroups; i++ ) {
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args.push( table[ levels[ i ] ] );
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}
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} else {
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groups = [];
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for ( i = 0; i < ngroups; i++ ) {
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args.push( arguments[ i ] );
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groups = groups.concat( repeat( i, arguments[ i ].length ) );
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}
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}
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if ( opts.alpha === void 0 ) {
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alpha = 0.05;
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} else {
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alpha = opts.alpha;
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}
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if ( alpha < 0.0 || alpha > 1.0 ) {
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throw new RangeError( 'invalid argument. Option `alpha` must be a number in the range 0 to 1. Value: `' + alpha + '`.' );
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}
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x = [];
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for ( i = 0; i < ngroups; i++ ) {
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if ( !isCollection( args[ i ] ) ) {
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throw new TypeError( 'invalid argument. Must provide array-like arguments. Value: `' + args[ i ] + '`.' );
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}
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if ( args[ i ].length === 0 ) {
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throw new Error( 'invalid argument. Supplied arrays cannot be empty. Value: `' + args[ i ] + '`.' );
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}
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loc = median( args[ i ] );
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for ( j = 0; j < args[ i ].length; j++ ) {
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args[ i ][ j ] -= loc;
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}
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x = x.concat( args[ i ] );
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}
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n = x.length;
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xabs = new Array( n );
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for ( i = 0; i < n; i++ ) {
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xabs[ i ] = abs( x[ i ] );
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}
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scores = ranks( xabs );
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a = new Array( n );
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mean = 0.0;
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M2 = 0.0;
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sums = repeat( 0.0, ngroups );
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for ( i = 0; i < n; i++ ) {
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a[ i ] = qnorm( ( 1.0 + ( scores[ i ]/(n+1) ) ) / 2.0, 0.0, 1.0 );
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sums[ ( levels ) ? indexOf( levels, groups[i] ) : groups[i] ] += a[ i ];
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delta = a[ i ] - mean;
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mean += delta / ( i+1 );
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M2 += delta * ( a[ i ] - mean );
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}
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variance = M2 / ( n - 1 );
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stat = 0.0;
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for ( i = 0; i < ngroups; i++ ) {
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stat += pow( sums[ i ], 2 ) / args[ i ].length;
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}
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stat = ( stat - ( n * pow( mean, 2 ) ) ) / variance;
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df = ngroups - 1;
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pval = 1.0 - chisqCDF( stat, df );
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out = {};
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setReadOnly( out, 'rejected', pval <= alpha );
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setReadOnly( out, 'alpha', alpha );
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setReadOnly( out, 'pValue', pval );
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setReadOnly( out, 'statistic', stat );
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setReadOnly( out, 'df', df );
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setReadOnly( out, 'method', 'Fligner-Killeen test of homogeneity of variances' );
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setReadOnly( out, 'print', print );
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return out;
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}
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// EXPORTS //
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module.exports = fligner;
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