time-to-botec

Benchmark sampling in different programming languages
Log | Files | Refs | README

README.md (4268B)


      1 <!--
      2 
      3 @license Apache-2.0
      4 
      5 Copyright (c) 2018 The Stdlib Authors.
      6 
      7 Licensed under the Apache License, Version 2.0 (the "License");
      8 you may not use this file except in compliance with the License.
      9 You may obtain a copy of the License at
     10 
     11    http://www.apache.org/licenses/LICENSE-2.0
     12 
     13 Unless required by applicable law or agreed to in writing, software
     14 distributed under the License is distributed on an "AS IS" BASIS,
     15 WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
     16 See the License for the specific language governing permissions and
     17 limitations under the License.
     18 
     19 -->
     20 
     21 # Logarithm of Cumulative Distribution Function
     22 
     23 > [Logistic][logistic-distribution] distribution logarithm of [cumulative distribution function][cdf].
     24 
     25 <section class="intro">
     26 
     27 The [cumulative distribution function][cdf] for a [logistic][logistic-distribution] random variable is
     28 
     29 <!-- <equation class="equation" label="eq:logistic_cdf" align="center" raw="F(x; \mu, s) = \frac{1}{1+e^{-\frac{x-\mu}{s}}}" alt="Cumulative distribution function for a logistic distribution."> -->
     30 
     31 <div class="equation" align="center" data-raw-text="F(x; \mu, s) = \frac{1}{1+e^{-\frac{x-\mu}{s}}}" data-equation="eq:logistic_cdf">
     32     <img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@51534079fef45e990850102147e8945fb023d1d0/lib/node_modules/@stdlib/stats/base/dists/logistic/logcdf/docs/img/equation_logistic_cdf.svg" alt="Cumulative distribution function for a logistic distribution.">
     33     <br>
     34 </div>
     35 
     36 <!-- </equation> -->
     37 
     38 where `mu` is the location parameter and `s > 0` is the scale parameter.
     39 
     40 </section>
     41 
     42 <!-- /.intro -->
     43 
     44 <section class="usage">
     45 
     46 ## Usage
     47 
     48 ```javascript
     49 var logcdf = require( '@stdlib/stats/base/dists/logistic/logcdf' );
     50 ```
     51 
     52 #### logcdf( x, mu, s )
     53 
     54 Evaluates the logarithm of the [cumulative distribution function][cdf] (CDF) for a [logistic][logistic-distribution] distribution with parameters `mu` (location parameter) and `s` (scale parameter).
     55 
     56 ```javascript
     57 var y = logcdf( 2.0, 0.0, 1.0 );
     58 // returns ~-0.127
     59 
     60 y = logcdf( 0.0, 0.0, 1.0 );
     61 // returns ~-0.693
     62 
     63 y = logcdf( -1.0, 4.0, 2.0 );
     64 // returns ~-2.579
     65 ```
     66 
     67 If provided `NaN` as any argument, the function returns `NaN`.
     68 
     69 ```javascript
     70 var y = logcdf( NaN, 0.0, 1.0 );
     71 // returns NaN
     72 
     73 y = logcdf( 0.0, NaN, 1.0 );
     74 // returns NaN
     75 
     76 y = logcdf( 0.0, 0.0, NaN );
     77 // returns NaN
     78 ```
     79 
     80 If provided `s < 0`, the function returns `NaN`.
     81 
     82 ```javascript
     83 var y = logcdf( 2.0, 0.0, -1.0 );
     84 // returns NaN
     85 ```
     86 
     87 If provided `s = 0`, the function evaluates the logarithm of the [CDF][cdf] of a [degenerate distribution][degenerate-distribution] centered at `mu`.
     88 
     89 ```javascript
     90 var y = logcdf( 2.0, 8.0, 0.0 );
     91 // returns -Infinity
     92 
     93 y = logcdf( 8.0, 8.0, 0.0 );
     94 // returns 0.0
     95 
     96 y = logcdf( 10.0, 8.0, 0.0 );
     97 // returns 0.0
     98 ```
     99 
    100 #### logcdf.factory( mu, s )
    101 
    102 Returns a function for evaluating the logarithm of the [cumulative distribution function][cdf] of a [logistic][logistic-distribution] distribution with parameters `mu` (location parameter) and `s` (scale parameter).
    103 
    104 ```javascript
    105 var mylogcdf = logcdf.factory( 10.0, 2.0 );
    106 
    107 var y = mylogcdf( 10.0 );
    108 // returns ~-0.693
    109 
    110 y = mylogcdf( 8.0 );
    111 // returns ~-1.313
    112 ```
    113 
    114 </section>
    115 
    116 <!-- /.usage -->
    117 
    118 <section class="notes">
    119 
    120 ## Notes
    121 
    122 -   In virtually all cases, using the `logpdf` or `logcdf` functions is preferable to manually computing the logarithm of the `pdf` or `cdf`, respectively, since the latter is prone to overflow and underflow.
    123 
    124 </section>
    125 
    126 <!-- /.notes -->
    127 
    128 <section class="examples">
    129 
    130 ## Examples
    131 
    132 <!-- eslint no-undef: "error" -->
    133 
    134 ```javascript
    135 var randu = require( '@stdlib/random/base/randu' );
    136 var logcdf = require( '@stdlib/stats/base/dists/logistic/logcdf' );
    137 
    138 var mu;
    139 var s;
    140 var x;
    141 var y;
    142 var i;
    143 
    144 for ( i = 0; i < 10; i++ ) {
    145     x = randu() * 10.0;
    146     mu = randu() * 10.0;
    147     s = randu() * 10.0;
    148     y = logcdf( x, mu, s );
    149     console.log( 'x: %d, µ: %d, s: %d, ln(F(x;µ,s)): %d', x, mu, s, y );
    150 }
    151 ```
    152 
    153 </section>
    154 
    155 <!-- /.examples -->
    156 
    157 <section class="links">
    158 
    159 [logistic-distribution]: https://en.wikipedia.org/wiki/Logistic_distribution
    160 
    161 [cdf]: https://en.wikipedia.org/wiki/Cumulative_distribution_function
    162 
    163 [degenerate-distribution]: https://en.wikipedia.org/wiki/Degenerate_distribution
    164 
    165 </section>
    166 
    167 <!-- /.links -->