time-to-botec

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

README.md (3315B)

      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 # incrmse
     22 
     23 > Compute the [mean squared error][mean-squared-error] (MSE) incrementally.
     24 
     25 <section class="intro">
     26 
     27 The [mean squared error][mean-squared-error] is defined as
     28 
     29 <!-- <equation class="equation" label="eq:mean_squared_error" align="center" raw="\operatorname{MSE} = \frac{1}{n} \sum_{i=0}^{n-1} (y_i - x_i)^2" alt="Equation for the mean squared error."> -->
     30 
     31 <div class="equation" align="center" data-raw-text="\operatorname{MSE} = \frac{1}{n} \sum_{i=0}^{n-1} (y_i - x_i)^2" data-equation="eq:mean_squared_error">
     32     <img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@f5d4f0cac0a117ba1e0c70706a2fb284f69e7291/lib/node_modules/@stdlib/stats/incr/mse/docs/img/equation_mean_squared_error.svg" alt="Equation for the mean squared error.">
     33     <br>
     34 </div>
     35 
     36 <!-- </equation> -->
     37 
     38 </section>
     39 
     40 <!-- /.intro -->
     41 
     42 <section class="usage">
     43 
     44 ## Usage
     45 
     46 ```javascript
     47 var incrmse = require( '@stdlib/stats/incr/mse' );
     48 ```
     49 
     50 #### incrmse()
     51 
     52 Returns an accumulator `function` which incrementally computes the [mean squared error][mean-squared-error].
     53 
     54 ```javascript
     55 var accumulator = incrmse();
     56 ```
     57 
     58 #### accumulator( \[x, y] )
     59 
     60 If provided input values `x` and `y`, the accumulator function returns an updated [mean squared error][mean-squared-error]. If not provided input values `x` and `y`, the accumulator function returns the current [mean squared error][mean-squared-error].
     61 
     62 ```javascript
     63 var accumulator = incrmse();
     64 
     65 var m = accumulator( 2.0, 3.0 );
     66 // returns 1.0
     67 
     68 m = accumulator( -1.0, -4.0 );
     69 // returns 5.0
     70 
     71 m = accumulator( -3.0, 5.0 );
     72 // returns ~24.67
     73 
     74 m = accumulator();
     75 // returns ~24.67
     76 ```
     77 
     78 </section>
     79 
     80 <!-- /.usage -->
     81 
     82 <section class="notes">
     83 
     84 ## Notes
     85 
     86 -   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.
     87 
     88 </section>
     89 
     90 <!-- /.notes -->
     91 
     92 <section class="examples">
     93 
     94 ## Examples
     95 
     96 <!-- eslint no-undef: "error" -->
     97 
     98 ```javascript
     99 var randu = require( '@stdlib/random/base/randu' );
    100 var incrmse = require( '@stdlib/stats/incr/mse' );
    101 
    102 var accumulator;
    103 var v1;
    104 var v2;
    105 var i;
    106 
    107 // Initialize an accumulator:
    108 accumulator = incrmse();
    109 
    110 // For each simulated datum, update the mean squared error...
    111 for ( i = 0; i < 100; i++ ) {
    112     v1 = ( randu()*100.0 ) - 50.0;
    113     v2 = ( randu()*100.0 ) - 50.0;
    114     accumulator( v1, v2 );
    115 }
    116 console.log( accumulator() );
    117 ```
    118 
    119 </section>
    120 
    121 <!-- /.examples -->
    122 
    123 <section class="links">
    124 
    125 [mean-squared-error]: https://en.wikipedia.org/wiki/Mean_squared_error
    126 
    127 </section>
    128 
    129 <!-- /.links -->