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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 isNonNegativeInteger = require( '@stdlib/math/base/assert/is-nonnegative-integer' );
var constantFunction = require( '@stdlib/utils/constant-function' );
var factorialln = require( '@stdlib/math/base/special/factorialln' );
var degenerate = require( '@stdlib/stats/base/dists/degenerate/pmf' ).factory;
var isnan = require( '@stdlib/math/base/assert/is-nan' );
var exp = require( '@stdlib/math/base/special/exp' );
var ln = require( '@stdlib/math/base/special/ln' );
var PINF = require( '@stdlib/constants/float64/pinf' );
// MAIN //
/**
* Returns a function for evaluating the probability mass function (PMF) for a Poisson distribution with mean parameter `lambda`.
*
* @param {NonNegativeNumber} lambda - mean parameter
* @returns {Function} PMF
*
* @example
* var pmf = factory( 1.0 );
* var y = pmf( 3.0 );
* // returns ~0.061
*
* y = pmf( 1.0 );
* // returns ~0.368
*/
function factory( lambda ) {
if ( isnan( lambda ) || lambda < 0.0 ) {
return constantFunction( NaN );
}
if ( lambda === 0.0 ) {
return degenerate( 0.0 );
}
return pmf;
/**
* Evaluates the probability mass function (PMF) for a Poisson distribution.
*
* @private
* @param {number} x - input value
* @returns {Probability} evaluated PMF
*
* @example
* var y = pmf( 2.0 );
* // returns <number>
*/
function pmf( x ) {
var lnl;
if ( isnan( x ) ) {
return NaN;
}
if ( isNonNegativeInteger( x ) && x !== PINF ) {
lnl = (x * ln( lambda )) - lambda - factorialln( x );
return exp( lnl );
}
return 0.0;
}
}
// EXPORTS //
module.exports = factory;
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