@stdlib/stats/base/dists/normal/quantile/lib/main.js

Standard library statistical functions.

/**
* @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 erfinv = require( '@stdlib/math/base/special/erfinv' );
var isnan = require( '@stdlib/math/base/assert/is-nan' );
var sqrt = require( '@stdlib/math/base/special/sqrt' );


// MAIN //

/**
* Evaluates the quantile function for a normal distribution with mean `mu` and standard deviation `sigma` at a probability `p`.
*
* @param {Probability} p - input value
* @param {number} mu - mean
* @param {NonNegativeNumber} sigma - standard deviation
* @returns {number} evaluated quantile function
*
* @example
* var y = quantile( 0.8, 0.0, 1.0 );
* // returns ~0.842
*
* @example
* var y = quantile( 0.5, 4.0, 2.0 );
* // returns 4.0
*
* @example
* var y = quantile( 1.1, 0.0, 1.0 );
* // returns NaN
*
* @example
* var y = quantile( -0.2, 0.0, 1.0 );
* // returns NaN
*
* @example
* var y = quantile( NaN, 0.0, 1.0 );
* // returns NaN
*
* @example
* var y = quantile( 0.0, NaN, 1.0 );
* // returns NaN
*
* @example
* var y = quantile( 0.0, 0.0, NaN );
* // returns NaN
*
* @example
* // Negative standard deviation:
* var y = quantile( 0.5, 0.0, -1.0 );
* // returns NaN
*/
function quantile( p, mu, sigma ) {
	var A;
	var B;

	if (
		isnan( mu ) ||
		isnan( sigma ) ||
		isnan( p ) ||
		sigma < 0.0 ||
		p < 0.0 ||
		p > 1.0
	) {
		return NaN;
	}
	if ( sigma === 0.0 ) {
		return mu;
	}
	A = mu;
	B = sigma * sqrt( 2.0 );
	return A + (B * erfinv( (2.0*p) - 1.0 ));
}


// EXPORTS //

module.exports = quantile;