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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 binomcoefln = require( '@stdlib/math/base/special/binomcoefln' );
var degenerate = require( '@stdlib/stats/base/dists/degenerate/logpmf' ).factory;
var isnan = require( '@stdlib/math/base/assert/is-nan' );
var log1p = require( '@stdlib/math/base/special/log1p' );
var ln = require( '@stdlib/math/base/special/ln' );
var NINF = require( '@stdlib/constants/float64/ninf' );
var PINF = require( '@stdlib/constants/float64/pinf' );
// MAIN //
/**
* Returns a function for evaluating the natural logarithm of the probability mass function (PMF) for a binomial distribution with number of trials `n` and success probability `p`.
*
* @param {NonNegativeInteger} n - number of trials
* @param {Probability} p - success probability
* @returns {Function} logPMF
*
* @example
* var logpmf = factory( 10, 0.5 );
* var y = logpmf( 3.0 );
* // returns ~-2.144
*
* y = logpmf( 5.0 );
* // returns ~-1.402
*/
function factory( n, p ) {
if (
isnan( n ) ||
isnan( p ) ||
!isNonNegativeInteger( n ) ||
n === PINF ||
p < 0.0 ||
p > 1.0
) {
return constantFunction( NaN );
}
if ( p === 0.0 || n === 0 ) {
return degenerate( 0.0 );
}
if ( p === 1.0 ) {
return degenerate( n );
}
return logpmf;
/**
* Evaluates the natural logarithm of the probability mass function (PMF) for a binomial distribution.
*
* @private
* @param {number} x - input value
* @returns {number} evaluated logPMF
*
* @example
* var y = logpmf( 2.0 );
* // returns <number>
*/
function logpmf( x ) {
var out;
if ( isnan( x ) ) {
return NaN;
}
if ( isNonNegativeInteger( x ) ) {
if ( x > n ) {
return NINF;
}
out = binomcoefln( n, x );
out += (x * ln( p )) + ((n - x) * log1p( -p ));
return out;
}
return NINF;
}
}
// EXPORTS //
module.exports = factory;
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