All files / stats/base/dists/negative-binomial/mgf/lib main.js

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/**
* @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 isnan = require( '@stdlib/math/base/assert/is-nan' );
var exp = require( '@stdlib/math/base/special/exp' );
var pow = require( '@stdlib/math/base/special/pow' );
var ln = require( '@stdlib/math/base/special/ln' );
 
 
// MAIN //
 
/**
* Evaluates the moment-generating function (MGF) for a negative binomial distribution.
*
* @param {number} t - input value
* @param {PositiveNumber} r - number of successes until experiment is stopped
* @param {Probability} p - success probability
* @returns {number} evaluated MGF
*
* @example
* var y = mgf( 0.05, 20.0, 0.8 );
* // returns ~267.839
*
* @example
* var y = mgf( 0.1, 20.0, 0.1 );
* // returns ~9.347
*
* @example
* var y = mgf( 0.5, 10.0, 0.4 );
* // returns ~42822.023
*
* @example
* var y = mgf( 0.1, 0.0, 0.5 );
* // returns NaN
*
* @example
* var y = mgf( 0.1, -2.0, 0.5 );
* // returns NaN
*
* @example
* var y = mgf( NaN, 20.0, 0.5 );
* // returns NaN
*
* @example
* var y = mgf( 0.0, NaN, 0.5 );
* // returns NaN
*
* @example
* var y = mgf( 0.0, 20.0, NaN );
* // returns NaN
*
* @example
* var y = mgf( 0.2, 20, -1.0 );
* // returns NaN
*
* @example
* var y = mgf( 0.2, 20, 1.5 );
* // returns NaN
*/
function mgf( t, r, p ) {
	if (
		isnan( t ) ||
		isnan( r ) ||
		isnan( p ) ||
		r <= 0.0 ||
		p < 0.0 ||
		p > 1.0 ||
		t >= -ln( p )
	) {
		return NaN;
	}
	return pow( ( (1.0 - p) * exp( t ) ) / ( 1.0 - (p * exp( t )) ), r );
}
 
 
// EXPORTS //
 
module.exports = mgf;