Press n or j to go to the next uncovered block, b, p or k for the previous block.
| 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 | 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x | /**
* @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 pow = require( '@stdlib/math/base/special/pow' );
var ln = require( '@stdlib/math/base/special/ln' );
var NINF = require( '@stdlib/constants/float64/ninf' );
// MAIN //
/**
* Evaluates the natural logarithm of the probability density function (PDF) for a Kumaraswamy's double bounded distribution with first shape parameter `a` and second shape parameter `b` at a value `x`.
*
* @param {number} x - input value
* @param {PositiveNumber} a - first shape parameter
* @param {PositiveNumber} b - second shape parameter
* @returns {number} evaluated logPDF
*
* @example
* var y = logpdf( 0.5, 1.0, 1.0 );
* // returns 0.0
*
* @example
* var y = logpdf( 0.5, 2.0, 4.0 );
* // returns ~0.523
*
* @example
* var y = logpdf( 0.2, 2.0, 2.0 );
* // returns ~-0.264
*
* @example
* var y = logpdf( 0.8, 4.0, 4.0 );
* // returns ~0.522
*
* @example
* var y = logpdf( -0.5, 4.0, 2.0 );
* // returns -Infinity
*
* @example
* var y = logpdf( 1.5, 4.0, 2.0 );
* // returns -Infinity
*
* @example
* var y = logpdf( 2.0, -1.0, 0.5 );
* // returns NaN
*
* @example
* var y = logpdf( 2.0, 0.5, -1.0 );
* // returns NaN
*
* @example
* var y = logpdf( NaN, 1.0, 1.0 );
* // returns NaN
*
* @example
* var y = logpdf( 0.0, NaN, 1.0 );
* // returns NaN
*
* @example
* var y = logpdf( 0.0, 1.0, NaN );
* // returns NaN
*/
function logpdf( x, a, b ) {
var out;
if (
isnan( x ) ||
isnan( a ) ||
isnan( b ) ||
a <= 0.0 ||
b <= 0.0
) {
return NaN;
}
if ( x <= 0.0 || x >= 1.0 ) {
return NINF;
}
out = ln( a*b );
out += ( a - 1.0 ) * ln( x );
out += ( b - 1.0 ) * ln( 1.0 - pow( x, a ) );
return out;
}
// EXPORTS //
module.exports = logpdf;
|