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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 | 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 constantFunction = require( '@stdlib/utils/constant-function' );
var exp = require( '@stdlib/math/base/special/exp' );
var pow = require( '@stdlib/math/base/special/pow' );
var isnan = require( '@stdlib/math/base/assert/is-nan' );
var sqrt = require( '@stdlib/math/base/special/sqrt' );
var normal = require( '@stdlib/stats/base/dists/normal/cdf' ).factory;
var PI = require( '@stdlib/constants/float64/pi' );
// VARIABLES //
var normalCDF = normal( 0.0, 1.0 );
// MAIN //
/**
* Returns a function for evaluating the probability density function (PDF) for a truncated normal distribution with endpoints `a` and `b`, mean `mu` and standard deviation `sigma`.
*
* @param {number} a - minimum support
* @param {number} b - maximum support
* @param {number} mu - location parameter
* @param {PositiveNumber} sigma - scale parameter
* @returns {Function} PDF
*
* @example
* var myPDF = factory( 0.0, 1.0, 0.0, 1.0 );
* var y = myPDF( 0.8 );
* // returns ~0.849
*
* @example
* var myPDF = factory( 0.0, 1.0, 0.5, 1.0 );
* var y = myPDF( 0.8 );
* // returns ~0.996
*
* @example
* var myPDF = factory( 0.0, 1.0, 0.0, 1.0 );
* var y = myPDF( 2.0 );
* // returns 0.0
*
* @example
* var myPDF = factory( 0.0, 1.0, 0.0, 1.0 );
* var y = myPDF( -1.0 );
* // returns 0.0
*/
function factory( a, b, mu, sigma ) {
var s2x2;
var A;
var B;
var C;
if (
isnan( a ) ||
isnan( b ) ||
isnan( mu ) ||
isnan( sigma ) ||
sigma <= 0.0 ||
a >= b
) {
return constantFunction( NaN );
}
s2x2 = 2.0 * pow( sigma, 2.0 );
A = 1.0 / ( sqrt( s2x2 * PI ) );
B = -1.0 / ( s2x2 );
C = normalCDF( (b-mu)/sigma ) - normalCDF( (a-mu)/sigma );
return pdf;
/**
* Evaluates the probability density function (PDF) for a truncated normal distribution.
*
* @private
* @param {number} x - input value
* @returns {number} evaluated PDF
*/
function pdf( x ) {
if ( isnan( x ) ) {
return NaN;
}
if ( x < a || x > b ) {
return 0.0;
}
return A * exp( B * pow( x - mu, 2.0 ) ) / C;
}
}
// EXPORTS //
module.exports = factory;
|