time-to-botec

main.js (5695B)

---

 /**
 * @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 isTypedArrayLike = require( '@stdlib/assert/is-typed-array-like' );
 var isNumber = require( '@stdlib/assert/is-number' );
 var isNumberArray = require( '@stdlib/assert/is-number-array' ).primitives;
 var setReadOnly = require( '@stdlib/utils/define-read-only-property' );
 var isFunction = require( '@stdlib/assert/is-function' );
 var isString = require( '@stdlib/assert/is-string' ).isPrimitive;
 var isnan = require( '@stdlib/assert/is-nan' );
 var max = require( './../../base/max' );
 var pKolmogorov1 = require( './smirnov.js' );
 var pKolmogorov = require( './marsaglia.js' );
 var ascending = require( './ascending.js' );
 var subtract = require( './subtract.js' );
 var validate = require( './validate.js' );
 var getCDF = require( './get_cdf.js' );
 var print = require( './print.js' ); // eslint-disable-line stdlib/no-redeclare
 
 
 // FUNCTIONS //
 
 var slice = Array.prototype.slice;
 
 
 // MAIN //
 
 /**
 * Computes a Kolmogorov-Smirnov goodness-of-fit test.
 *
 * @param {NumericArray} x - input array holding numeric values
 * @param {(Function|string)} y - either a CDF function or a string denoting the name of a distribution
 * @param {...number} [params] - distribution parameters passed to reference CDF
 * @param {Options} [options] - function options
 * @param {number} [options.alpha=0.05] - significance level
 * @param {boolean} [options.sorted=false] - boolean indicating if the input array is already in sorted order
 * @param {string} [options.alternative="two-sided"] - string indicating whether to conduct two-sided or one-sided hypothesis test (other options: `less`, `greater`)
 * @throws {TypeError} argument x has to be a typed array or array of numbers
 * @throws {TypeError} argument y has to be a CDF function or string
 * @throws {TypeError} options has to be simple object
 * @throws {TypeError} alpha option has to be a number primitive
 * @throws {RangeError} alpha option has to be a number in the interval `[0,1]`
 * @throws {TypeError} alternative option has to be a string primitive
 * @throws {Error} alternative option must be `two-sided`, `less` or `greater`
 * @throws {TypeError} sorted option has to be a boolean primitive
 * @returns {Object} test result object
 *
 * @example
 * var out = kstest( [ 2.0, 1.0, 5.0, -5.0, 3.0, 0.5, 6.0 ], 'normal', 0.0, 1.0 );
 * // returns { 'pValue': ~0.015, 'statistic': ~0.556, ... }
 */
 function kstest() {
 	var nDistParams;
 	var distParams;
 	var distArgs;
 	var options;
 	var alpha;
 	var opts;
 	var pval;
 	var stat;
 	var yVal;
 	var alt;
 	var err;
 	var idx;
 	var out;
 	var val;
 	var i;
 	var n;
 	var x;
 	var y;
 
 	x = arguments[ 0 ];
 	y = arguments[ 1 ];
 	if ( !isNumberArray( x ) && !isTypedArrayLike( x ) ) {
 		throw new TypeError( 'invalid argument. First argument must be a typed array or number array. Value: `' + x + '`.' );
 	}
 	if ( !isFunction( y ) && !isString( y ) ) {
 		throw new TypeError( 'invalid argument. Second argument must be either a CDF function or a string primitive. Value: `' + y + '`' );
 	}
 	if ( isString( y ) ) {
 		y = getCDF( y );
 	}
 	nDistParams = y.length - 1.0;
 	n = x.length;
 
 	distParams = new Array( nDistParams );
 	for ( i = 0; i < nDistParams; i++ ) {
 		idx = i + 2;
 		val = arguments[ idx ];
 		if ( !isNumber( val ) || isnan( val ) ) {
 			throw new TypeError( 'invalid argument. Distribution parameter must be a number primitive. Value: `' + val + '`.' );
 		}
 		distParams[ i ] = arguments[ idx ];
 	}
 	opts = {};
 	if ( arguments.length > 2 + nDistParams ) {
 		options = arguments[ 2 + nDistParams ];
 		err = validate( opts, options );
 		if ( err ) {
 			throw err;
 		}
 	}
 	// Make a copy to prevent mutation of x:
 	x = slice.call( x );
 
 	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 + '`.' );
 	}
 
 	// Input data has to be sorted:
 	if ( opts.sorted !== true ) {
 		x.sort( ascending );
 	}
 	distArgs = [ null ].concat( distParams );
 	for ( i = 0; i < n; i++ ) {
 		distArgs[ 0 ] = x[ i ];
 		yVal = y.apply( null, distArgs );
 		x[ i ] = yVal - ( i / n );
 	}
 
 	alt = opts.alternative || 'two-sided';
 	switch ( alt ) {
 	case 'two-sided':
 		stat = max( n, [ max( n, x, 1 ), max( n, subtract( 1/n, x ), 1 ) ], 1 );
 		break;
 	case 'greater':
 		stat = max( n, subtract( 1/n, x ), 1 );
 		break;
 	case 'less':
 		stat = max( n, x, 1 );
 		break;
 	default:
 		throw new Error( 'Invalid option. `alternative` must be either `two-sided`, `less` or `greater`. Value: `' + alt + '`' );
 	}
 	if ( alt === 'two-sided' ) {
 		pval = 1.0 - pKolmogorov( stat, n );
 	} else {
 		pval = 1.0 - pKolmogorov1( stat, n );
 	}
 
 	out = {};
 	setReadOnly( out, 'rejected', pval <= alpha );
 	setReadOnly( out, 'alpha', alpha );
 	setReadOnly( out, 'pValue', pval );
 	setReadOnly( out, 'statistic', stat );
 	setReadOnly( out, 'method', 'Kolmogorov-Smirnov goodness-of-fit test' );
 	setReadOnly( out, 'print', print );
 	setReadOnly( out, 'alternative', alt );
 	return out;
 }
 
 
 // EXPORTS //
 
 module.exports = kstest;