time-to-botec

Benchmark sampling in different programming languages
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README.md (3978B)

      1 <!--
      2 
      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.
     18 
     19 -->
     20 
     21 # incrmpe
     22 
     23 > Compute the [mean percentage error][mean-percentage-error] (MPE) incrementally.
     24 
     25 <section class="intro">
     26 
     27 The [mean percentage error][mean-percentage-error] is defined as
     28 
     29 <!-- <equation class="equation" label="eq:mean_percentage_error" align="center" raw="\operatorname{MPE}  = \frac{100}{n} \sum_{i=0}^{n-1} \frac{a_i - f_i}{a_i}" alt="Equation for the mean percentage error."> -->
     30 
     31 <div class="equation" align="center" data-raw-text="\operatorname{MPE}  = \frac{100}{n} \sum_{i=0}^{n-1} \frac{a_i - f_i}{a_i}" data-equation="eq:mean_percentage_error">
     32     <img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@2acedf866c9a4f1353af22f95780535612c5ee06/lib/node_modules/@stdlib/stats/incr/mpe/docs/img/equation_mean_percentage_error.svg" alt="Equation for the mean 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 incrmpe = require( '@stdlib/stats/incr/mpe' );
     50 ```
     51 
     52 #### incrmpe()
     53 
     54 Returns an accumulator `function` which incrementally computes the [mean percentage error][mean-percentage-error].
     55 
     56 ```javascript
     57 var accumulator = incrmpe();
     58 ```
     59 
     60 #### accumulator( \[f, a] )
     61 
     62 If provided input values `f` and `a`, the accumulator function returns an updated [mean percentage error][mean-percentage-error]. If not provided input values `f` and `a`, the accumulator function returns the current [mean percentage error][mean-percentage-error].
     63 
     64 ```javascript
     65 var accumulator = incrmpe();
     66 
     67 var m = accumulator( 2.0, 3.0 );
     68 // returns ~33.33
     69 
     70 m = accumulator( 1.0, 4.0 );
     71 // returns ~54.17
     72 
     73 m = accumulator( 3.0, 5.0 );
     74 // returns ~49.44
     75 
     76 m = accumulator();
     77 // returns ~49.44
     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 -   Be careful when interpreting the [mean percentage error][mean-percentage-error] as errors can cancel. This stated, that errors can cancel makes the [mean percentage error][mean-percentage-error] suitable for measuring the bias in forecasts. 
     90 -   **Warning**: the [mean percentage error][mean-percentage-error] is **not** suitable for intermittent demand patterns (i.e., when `a_i` is `0`). Interpretation is most straightforward when actual and forecast values are positive valued (e.g., number of widgets sold). 
     91 
     92 </section>
     93 
     94 <!-- /.notes -->
     95 
     96 <section class="examples">
     97 
     98 ## Examples
     99 
    100 <!-- eslint no-undef: "error" -->
    101 
    102 ```javascript
    103 var randu = require( '@stdlib/random/base/randu' );
    104 var incrmpe = require( '@stdlib/stats/incr/mpe' );
    105 
    106 var accumulator;
    107 var v1;
    108 var v2;
    109 var i;
    110 
    111 // Initialize an accumulator:
    112 accumulator = incrmpe();
    113 
    114 // For each simulated datum, update the mean percentage error...
    115 for ( i = 0; i < 100; i++ ) {
    116     v1 = ( randu()*100.0 ) + 50.0;
    117     v2 = ( randu()*100.0 ) + 50.0;
    118     accumulator( v1, v2 );
    119 }
    120 console.log( accumulator() );
    121 ```
    122 
    123 </section>
    124 
    125 <!-- /.examples -->
    126 
    127 <section class="links">
    128 
    129 [mean-percentage-error]: https://en.wikipedia.org/wiki/Mean_percentage_error
    130 
    131 </section>
    132 
    133 <!-- /.links -->