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 | 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 2011x 2011x 2011x 1x 1x 1x 1x 1x | /** * @license Apache-2.0 * * Copyright (c) 2025 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 addon = require( './../src/addon.node' ); // MAIN // /** * Evaluates the probability mass function (PMF) for a Planck (discrete exponential) distribution with shape parameter `lambda` . * * @private * @param {number} x - input value (integer) * @param {number} lambda - shape parameter * @returns {Probability} evaluated PMF * * @example * var y = pmf( 4.0, 0.3 ); * // returns ~0.0781 * * @example * var y = pmf( 2.0, 1.7 ); * // returns ~0.0273 * * @example * var y = pmf( -1.0, 2.5 ); * // returns 0.0 * * @example * var y = pmf( NaN, 0.0 ); * // returns NaN * * @example * var y = pmf( 0.0, NaN ); * // returns NaN * * @example * var y = pmf( 2.0, -1.0 ); * // returns NaN */ function pmf( x, lambda ) { return addon( x, lambda ); } // EXPORTS // module.exports = pmf; |