time-to-botec

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

README.md (6726B)


      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 # Arcsine
     22 
     23 > Arcsine distribution.
     24 
     25 <section class="usage">
     26 
     27 ## Usage
     28 
     29 ```javascript
     30 var arcsine = require( '@stdlib/stats/base/dists/arcsine' );
     31 ```
     32 
     33 #### arcsine
     34 
     35 [Arcsine][arcsine-distribution] distribution.
     36 
     37 ```javascript
     38 var dist = arcsine;
     39 // returns {...}
     40 ```
     41 
     42 The namespace contains the following distribution functions:
     43 
     44 <!-- <toc pattern="*+(cdf|pdf|mgf|quantile)*"> -->
     45 
     46 <div class="namespace-toc">
     47 
     48 -   <span class="signature">[`cdf( x, a, b )`][@stdlib/stats/base/dists/arcsine/cdf]</span><span class="delimiter">: </span><span class="description">arcsine distribution cumulative distribution function.</span>
     49 -   <span class="signature">[`logcdf( x, a, b )`][@stdlib/stats/base/dists/arcsine/logcdf]</span><span class="delimiter">: </span><span class="description">arcsine distribution logarithm of cumulative distribution function.</span>
     50 -   <span class="signature">[`logpdf( x, a, b )`][@stdlib/stats/base/dists/arcsine/logpdf]</span><span class="delimiter">: </span><span class="description">arcsine distribution logarithm of probability density function (PDF).</span>
     51 -   <span class="signature">[`pdf( x, a, b )`][@stdlib/stats/base/dists/arcsine/pdf]</span><span class="delimiter">: </span><span class="description">arcsine distribution probability density function (PDF).</span>
     52 -   <span class="signature">[`quantile( p, a, b )`][@stdlib/stats/base/dists/arcsine/quantile]</span><span class="delimiter">: </span><span class="description">arcsine distribution quantile function.</span>
     53 
     54 </div>
     55 
     56 <!-- </toc> -->
     57 
     58 The namespace contains the following functions for calculating distribution properties:
     59 
     60 <!-- <toc pattern="*+(entropy|kurtosis|mean|median|mode|skewness|stdev|variance)*"> -->
     61 
     62 <div class="namespace-toc">
     63 
     64 -   <span class="signature">[`entropy( a, b )`][@stdlib/stats/base/dists/arcsine/entropy]</span><span class="delimiter">: </span><span class="description">arcsine distribution differential entropy.</span>
     65 -   <span class="signature">[`kurtosis( a, b )`][@stdlib/stats/base/dists/arcsine/kurtosis]</span><span class="delimiter">: </span><span class="description">arcsine distribution excess kurtosis.</span>
     66 -   <span class="signature">[`mean( a, b )`][@stdlib/stats/base/dists/arcsine/mean]</span><span class="delimiter">: </span><span class="description">arcsine distribution expected value.</span>
     67 -   <span class="signature">[`median( a, b )`][@stdlib/stats/base/dists/arcsine/median]</span><span class="delimiter">: </span><span class="description">arcsine distribution median.</span>
     68 -   <span class="signature">[`mode( a, b )`][@stdlib/stats/base/dists/arcsine/mode]</span><span class="delimiter">: </span><span class="description">arcsine distribution mode.</span>
     69 -   <span class="signature">[`skewness( a, b )`][@stdlib/stats/base/dists/arcsine/skewness]</span><span class="delimiter">: </span><span class="description">arcsine distribution skewness.</span>
     70 -   <span class="signature">[`stdev( a, b )`][@stdlib/stats/base/dists/arcsine/stdev]</span><span class="delimiter">: </span><span class="description">arcsine distribution standard deviation.</span>
     71 -   <span class="signature">[`variance( a, b )`][@stdlib/stats/base/dists/arcsine/variance]</span><span class="delimiter">: </span><span class="description">arcsine distribution variance.</span>
     72 
     73 </div>
     74 
     75 <!-- </toc> -->
     76 
     77 The namespace contains a constructor function for creating an [arcsine][arcsine-distribution] distribution object.
     78 
     79 <!-- <toc pattern="*ctor*"> -->
     80 
     81 <div class="namespace-toc">
     82 
     83 -   <span class="signature">[`Arcsine( [a, b] )`][@stdlib/stats/base/dists/arcsine/ctor]</span><span class="delimiter">: </span><span class="description">arcsine distribution constructor.</span>
     84 
     85 </div>
     86 
     87 <!-- </toc> -->
     88 
     89 ```javascript
     90 var Arcsine = require( '@stdlib/stats/base/dists/arcsine' ).Arcsine;
     91 var dist = new Arcsine( 2.0, 4.0 );
     92 
     93 var mu = dist.mean;
     94 // returns 3.0
     95 ```
     96 
     97 </section>
     98 
     99 <!-- /.usage -->
    100 
    101 <section class="examples">
    102 
    103 ## Examples
    104 
    105 <!-- TODO: better examples -->
    106 
    107 <!-- eslint no-undef: "error" -->
    108 
    109 ```javascript
    110 var objectKeys = require( '@stdlib/utils/keys' );
    111 var arcsine = require( '@stdlib/stats/base/dists/arcsine' );
    112 
    113 console.log( objectKeys( arcsine ) );
    114 ```
    115 
    116 </section>
    117 
    118 <!-- /.examples -->
    119 
    120 <section class="links">
    121 
    122 [arcsine-distribution]: https://en.wikipedia.org/wiki/Arcsine_distribution
    123 
    124 <!-- <toc-links> -->
    125 
    126 [@stdlib/stats/base/dists/arcsine/ctor]: https://www.npmjs.com/package/@stdlib/stats/tree/main/base/dists/arcsine/ctor
    127 
    128 [@stdlib/stats/base/dists/arcsine/entropy]: https://www.npmjs.com/package/@stdlib/stats/tree/main/base/dists/arcsine/entropy
    129 
    130 [@stdlib/stats/base/dists/arcsine/kurtosis]: https://www.npmjs.com/package/@stdlib/stats/tree/main/base/dists/arcsine/kurtosis
    131 
    132 [@stdlib/stats/base/dists/arcsine/mean]: https://www.npmjs.com/package/@stdlib/stats/tree/main/base/dists/arcsine/mean
    133 
    134 [@stdlib/stats/base/dists/arcsine/median]: https://www.npmjs.com/package/@stdlib/stats/tree/main/base/dists/arcsine/median
    135 
    136 [@stdlib/stats/base/dists/arcsine/mode]: https://www.npmjs.com/package/@stdlib/stats/tree/main/base/dists/arcsine/mode
    137 
    138 [@stdlib/stats/base/dists/arcsine/skewness]: https://www.npmjs.com/package/@stdlib/stats/tree/main/base/dists/arcsine/skewness
    139 
    140 [@stdlib/stats/base/dists/arcsine/stdev]: https://www.npmjs.com/package/@stdlib/stats/tree/main/base/dists/arcsine/stdev
    141 
    142 [@stdlib/stats/base/dists/arcsine/variance]: https://www.npmjs.com/package/@stdlib/stats/tree/main/base/dists/arcsine/variance
    143 
    144 [@stdlib/stats/base/dists/arcsine/cdf]: https://www.npmjs.com/package/@stdlib/stats/tree/main/base/dists/arcsine/cdf
    145 
    146 [@stdlib/stats/base/dists/arcsine/logcdf]: https://www.npmjs.com/package/@stdlib/stats/tree/main/base/dists/arcsine/logcdf
    147 
    148 [@stdlib/stats/base/dists/arcsine/logpdf]: https://www.npmjs.com/package/@stdlib/stats/tree/main/base/dists/arcsine/logpdf
    149 
    150 [@stdlib/stats/base/dists/arcsine/pdf]: https://www.npmjs.com/package/@stdlib/stats/tree/main/base/dists/arcsine/pdf
    151 
    152 [@stdlib/stats/base/dists/arcsine/quantile]: https://www.npmjs.com/package/@stdlib/stats/tree/main/base/dists/arcsine/quantile
    153 
    154 <!-- </toc-links> -->
    155 
    156 </section>
    157 
    158 <!-- /.links -->