159 lines
4.4 KiB
JavaScript
159 lines
4.4 KiB
JavaScript
|
/**
|
|||
|
* @license Apache-2.0
|
|||
|
*
|
|||
|
* Copyright (c) 2018 The Stdlib Authors.
|
|||
|
*
|
|||
|
* 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.
|
|||
|
*/
|
|||
|
|
|||
|
'use strict';
|
|||
|
|
|||
|
// MODULES //
|
|||
|
|
|||
|
var isCollection = require( '@stdlib/assert/is-collection' );
|
|||
|
var isPlainObject = require( '@stdlib/assert/is-plain-object' );
|
|||
|
var setReadOnly = require( '@stdlib/utils/define-read-only-property' );
|
|||
|
var objectKeys = require( '@stdlib/utils/keys' );
|
|||
|
var chisqCDF = require( './../../base/dists/chisquare/cdf' );
|
|||
|
var group = require( '@stdlib/utils/group' );
|
|||
|
var ln = require( '@stdlib/math/base/special/ln' );
|
|||
|
var variance = require( './variance.js' );
|
|||
|
var validate = require( './validate.js' );
|
|||
|
var print = require( './print.js' ); // eslint-disable-line stdlib/no-redeclare
|
|||
|
|
|||
|
|
|||
|
// MAIN //
|
|||
|
|
|||
|
/**
|
|||
|
* Computes Bartlett’s test for equal variances.
|
|||
|
*
|
|||
|
* @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
|
|||
|
* @param {Options} [options] - function options
|
|||
|
* @param {number} [options.alpha=0.05] - significance level
|
|||
|
* @param {Array} [options.groups] - array of group indicators
|
|||
|
* @throws {TypeError} must provide array-like arguments
|
|||
|
* @throws {RangeError} alpha option has to be a number in the interval `[0,1]`
|
|||
|
* @throws {Error} must provide at least two array-like arguments if `groups` is not set
|
|||
|
* @throws {TypeError} options has to be simple object
|
|||
|
* @throws {TypeError} must provide valid options
|
|||
|
* @returns {Object} test results
|
|||
|
*
|
|||
|
* @example
|
|||
|
* // Data from Hollander & Wolfe (1973), p. 116:
|
|||
|
* var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];
|
|||
|
* var y = [ 3.8, 2.7, 4.0, 2.4 ];
|
|||
|
* var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];
|
|||
|
*
|
|||
|
* var out = bartlett( x, y, z );
|
|||
|
* // returns {...}
|
|||
|
*/
|
|||
|
function bartlett() {
|
|||
|
var options;
|
|||
|
var ngroups;
|
|||
|
var ninvSum;
|
|||
|
var levels;
|
|||
|
var table;
|
|||
|
var alpha;
|
|||
|
var nSum;
|
|||
|
var vSum;
|
|||
|
var args;
|
|||
|
var opts;
|
|||
|
var pval;
|
|||
|
var stat;
|
|||
|
var arg;
|
|||
|
var err;
|
|||
|
var lnv;
|
|||
|
var out;
|
|||
|
var df;
|
|||
|
var n;
|
|||
|
var v;
|
|||
|
var i;
|
|||
|
|
|||
|
args = [];
|
|||
|
ngroups = arguments.length;
|
|||
|
opts = {};
|
|||
|
if ( isPlainObject( arguments[ ngroups - 1 ] ) ) {
|
|||
|
options = arguments[ ngroups - 1 ];
|
|||
|
ngroups -= 1;
|
|||
|
err = validate( opts, options );
|
|||
|
if ( err ) {
|
|||
|
throw err;
|
|||
|
}
|
|||
|
}
|
|||
|
if ( opts.groups ) {
|
|||
|
table = group( arguments[ 0 ], opts.groups );
|
|||
|
levels = objectKeys( table );
|
|||
|
ngroups = levels.length;
|
|||
|
if ( ngroups < 2 ) {
|
|||
|
throw new Error( 'invalid number of groups. `groups` array must contain at least two unique elements. Value: `' + levels + '`.' );
|
|||
|
}
|
|||
|
for ( i = 0; i < ngroups; i++ ) {
|
|||
|
args.push( table[ levels[ i ] ] );
|
|||
|
}
|
|||
|
} else {
|
|||
|
for ( i = 0; i < ngroups; i++ ) {
|
|||
|
args.push( arguments[ i ] );
|
|||
|
}
|
|||
|
}
|
|||
|
nSum = 0;
|
|||
|
ninvSum = 0.0;
|
|||
|
vSum = 0.0;
|
|||
|
lnv = 0.0;
|
|||
|
n = new Array( ngroups );
|
|||
|
v = n.slice();
|
|||
|
for ( i = 0; i < ngroups; i++ ) {
|
|||
|
arg = args[ i ];
|
|||
|
if ( !isCollection( arg ) ) {
|
|||
|
throw new TypeError( 'invalid argument. Must provide array-like arguments. Value: `' + arg + '`.' );
|
|||
|
}
|
|||
|
if ( arg.length === 0 ) {
|
|||
|
throw new Error( 'invalid argument. Supplied arrays cannot be empty. Value: `' + arg + '`.' );
|
|||
|
}
|
|||
|
n[ i ] = arg.length - 1;
|
|||
|
nSum += n[ i ];
|
|||
|
ninvSum += 1.0 / n[ i ];
|
|||
|
v[ i ] = variance( arg );
|
|||
|
vSum += ( n[ i ] * v[ i ] );
|
|||
|
lnv += n[ i ] * ln( v[ i ] );
|
|||
|
}
|
|||
|
vSum /= nSum;
|
|||
|
if ( opts.alpha === void 0 ) {
|
|||
|
alpha = 0.05;
|
|||
|
} else {
|
|||
|
alpha = opts.alpha;
|
|||
|
}
|
|||
|
if ( alpha < 0.0 || alpha > 1.0 ) {
|
|||
|
throw new RangeError( 'invalid argument. Option `alpha` must be a number in the range 0 to 1. Value: `' + alpha + '`.' );
|
|||
|
}
|
|||
|
|
|||
|
stat = ( ( nSum * ln( vSum ) ) - lnv );
|
|||
|
stat /= ( 1.0 + ( ( ninvSum - ( 1.0 / nSum ) ) / ( 3 * ( ngroups-1 ) ) ) );
|
|||
|
df = ngroups - 1;
|
|||
|
pval = 1.0 - chisqCDF( stat, df );
|
|||
|
|
|||
|
out = {};
|
|||
|
setReadOnly( out, 'rejected', pval <= alpha );
|
|||
|
setReadOnly( out, 'alpha', alpha );
|
|||
|
setReadOnly( out, 'pValue', pval );
|
|||
|
setReadOnly( out, 'statistic', stat );
|
|||
|
setReadOnly( out, 'df', df );
|
|||
|
setReadOnly( out, 'method', 'Bartlett\'s test of equal variances' );
|
|||
|
setReadOnly( out, 'print', print );
|
|||
|
return out;
|
|||
|
}
|
|||
|
|
|||
|
|
|||
|
// EXPORTS //
|
|||
|
|
|||
|
module.exports = bartlett;
|