time-to-botec

Benchmark sampling in different programming languages
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README.md (4368B)

      1 <!--
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      3 @license Apache-2.0
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      5 Copyright (c) 2018 The Stdlib Authors.
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      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
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     11    http://www.apache.org/licenses/LICENSE-2.0
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     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.
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     19 -->
     20 
     21 # incrmaape
     22 
     23 > Compute the [mean arctangent absolute percentage error][@kim:2016a] (MAAPE) incrementally.
     24 
     25 <section class="intro">
     26 
     27 The [mean arctangent absolute percentage error][@kim:2016a] is defined as
     28 
     29 <!-- <equation class="equation" label="eq:mean_arctangent_absolute_percentage_error" align="center" raw="\operatorname{MAAPE}  = \frac{1}{n} \sum_{i=0}^{n-1} \operatorname{arctan}\biggl( \biggl| \frac{a_i - f_i}{a_i} \biggr| \biggr)" alt="Equation for the mean arctangent absolute percentage error."> -->
     30 
     31 <div class="equation" align="center" data-raw-text="\operatorname{MAAPE}  = \frac{1}{n} \sum_{i=0}^{n-1} \operatorname{arctan} \biggl( \biggl| \frac{a_i - f_i}{a_i} \biggr| \biggr)" data-equation="eq:mean_arctangent_absolute_percentage_error">
     32     <img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@d40d38b97af0f02f0fcc47100c3ebaca25db7c0d/lib/node_modules/@stdlib/stats/incr/maape/docs/img/equation_mean_arctangent_absolute_percentage_error.svg" alt="Equation for the mean arctangent absolute percentage error.">
     33     <br>
     34 </div>
     35 
     36 <!-- </equation> -->
     37 
     38 where `f_i` is the forecast value and `a_i` is the actual value.
     39 
     40 </section>
     41 
     42 <!-- /.intro -->
     43 
     44 <section class="usage">
     45 
     46 ## Usage
     47 
     48 ```javascript
     49 var incrmaape = require( '@stdlib/stats/incr/maape' );
     50 ```
     51 
     52 #### incrmaape()
     53 
     54 Returns an accumulator `function` which incrementally computes the [mean arctangent absolute percentage error][@kim:2016a].
     55 
     56 ```javascript
     57 var accumulator = incrmaape();
     58 ```
     59 
     60 #### accumulator( \[f, a] )
     61 
     62 If provided input values `f` and `a`, the accumulator function returns an updated [mean arctangent absolute percentage error][@kim:2016a]. If not provided input values `f` and `a`, the accumulator function returns the current [mean arctangent absolute percentage error][@kim:2016a].
     63 
     64 ```javascript
     65 var accumulator = incrmaape();
     66 
     67 var m = accumulator( 2.0, 3.0 );
     68 // returns ~0.3218
     69 
     70 m = accumulator( 1.0, 4.0 );
     71 // returns ~0.4826
     72 
     73 m = accumulator( 3.0, 5.0 );
     74 // returns ~0.4486
     75 
     76 m = accumulator();
     77 // returns ~0.4486
     78 ```
     79 
     80 </section>
     81 
     82 <!-- /.usage -->
     83 
     84 <section class="notes">
     85 
     86 ## Notes
     87 
     88 -   Input values are **not** type checked. If provided `NaN` or a value which, when used in computations, results in `NaN`, the accumulated value is `NaN` for **all** future invocations. If non-numeric inputs are possible, you are advised to type check and handle accordingly **before** passing the value to the accumulator function.
     89 -   Note that, unlike the [mean absolute percentage error][@stdlib/stats/incr/mape] (MAPE), the [mean arctangent absolute percentage error][@kim:2016a] is expressed in radians on the interval \[0,π/2].
     90 
     91 </section>
     92 
     93 <!-- /.notes -->
     94 
     95 <section class="examples">
     96 
     97 ## Examples
     98 
     99 <!-- eslint no-undef: "error" -->
    100 
    101 ```javascript
    102 var randu = require( '@stdlib/random/base/randu' );
    103 var incrmaape = require( '@stdlib/stats/incr/maape' );
    104 
    105 var accumulator;
    106 var v1;
    107 var v2;
    108 var i;
    109 
    110 // Initialize an accumulator:
    111 accumulator = incrmaape();
    112 
    113 // For each simulated datum, update the mean arctangent absolute percentage error...
    114 for ( i = 0; i < 100; i++ ) {
    115     v1 = ( randu()*100.0 ) + 50.0;
    116     v2 = ( randu()*100.0 ) + 50.0;
    117     accumulator( v1, v2 );
    118 }
    119 console.log( accumulator() );
    120 ```
    121 
    122 </section>
    123 
    124 <!-- /.examples -->
    125 
    126 <section class="references">
    127 
    128 ## References
    129 
    130 -   Kim, Sungil, and Heeyoung Kim. 2016. "A new metric of absolute percentage error for intermittent demand forecasts." _International Journal of Forecasting_ 32 (3): 669–79. doi:[10.1016/j.ijforecast.2015.12.003][@kim:2016a].
    131 
    132 </section>
    133 
    134 <!-- /.references -->
    135 
    136 <section class="links">
    137 
    138 [@kim:2016a]: https://www.sciencedirect.com/science/article/pii/S0169207016000121
    139 
    140 [@stdlib/stats/incr/mape]: https://www.npmjs.com/package/@stdlib/stats/tree/main/incr/mape
    141 
    142 </section>
    143 
    144 <!-- /.links -->