All files main.js

100% Statements 73/73
100% Branches 6/6
100% Functions 1/1
100% Lines 73/73

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 741x 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 1108x 1108x 1108x 1108x 1108x 1105x 1108x 8x 8x 1100x 1100x 1108x 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 exp = require( '@stdlib/math/base/special/exp' );
var expm1 = require( '@stdlib/math/base/special/expm1' );
 
 
// MAIN //
 
/**
* Returns the variance for a lognormal distribution with location `mu` and scale `sigma`.
*
* @param {number} mu - location parameter
* @param {PositiveNumber} sigma - scale parameter
* @returns {NonNegativeNumber} variance
*
* @example
* var y = variance( 0.0, 1.0 );
* // returns ~4.671
*
* @example
* var y = variance( 5.0, 2.0 );
* // returns ~64457364.853
*
* @example
* var y = variance( NaN, 1.0 );
* // returns NaN
*
* @example
* var y = variance( 0.0, NaN );
* // returns NaN
*
* @example
* var y = variance( 0.0, 0.0 );
* // returns NaN
*/
function variance( mu, sigma ) {
	var s2;
	if (
		isnan( mu ) ||
		isnan( sigma ) ||
		sigma <= 0.0
	) {
		return NaN;
	}
	s2 = sigma*sigma;
	return expm1( s2 ) * exp( ( 2.0*mu ) + s2 );
}
 
 
// EXPORTS //
 
module.exports = variance;