time-to-botec

README.md (5268B)

---

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 @license Apache-2.0
 
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 you may not use this file except in compliance with the License.
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 See the License for the specific language governing permissions and
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 # incrmeanvar
 
 > Compute an [arithmetic mean][arithmetic-mean] and an [unbiased sample variance][sample-variance] incrementally.
 
 <section class="intro">
 
 The [arithmetic mean][arithmetic-mean] is defined as
 
 <!-- <equation class="equation" label="eq:arithmetic_mean" align="center" raw="\bar{x} = \frac{1}{n} \sum_{i=0}^{n-1} x_i" alt="Equation for the arithmetic mean."> -->
 
 <div class="equation" align="center" data-raw-text="\bar{x} = \frac{1}{n} \sum_{i=0}^{n-1} x_i" data-equation="eq:arithmetic_mean">
     <img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@b2df03cb2a582cf1df289c3ddca6922c0db854b4/lib/node_modules/@stdlib/stats/incr/meanvar/docs/img/equation_arithmetic_mean.svg" alt="Equation for the arithmetic mean.">
     <br>
 </div>
 
 <!-- </equation> -->
 
 and the [unbiased sample variance][sample-variance] is defined as
 
 <!-- <equation class="equation" label="eq:unbiased_sample_variance" align="center" raw="s^2 = \frac{1}{n-1} \sum_{i=0}^{n-1} ( x_i - \bar{x} )^2" alt="Equation for the unbiased sample variance."> -->
 
 <div class="equation" align="center" data-raw-text="s^2 = \frac{1}{n-1} \sum_{i=0}^{n-1} ( x_i - \bar{x} )^2" data-equation="eq:unbiased_sample_variance">
     <img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@eafa6e61d15b7c712c9288d59d8e0e3f0aa6c011/lib/node_modules/@stdlib/stats/incr/meanvar/docs/img/equation_unbiased_sample_variance.svg" alt="Equation for the unbiased sample variance.">
     <br>
 </div>
 
 <!-- </equation> -->
 
 <section class="usage">
 
 ## Usage
 
 ```javascript
 var incrmeanvar = require( '@stdlib/stats/incr/meanvar' );
 ```
 
 #### incrmeanvar( \[out] )
 
 Returns an accumulator `function` which incrementally computes an [arithmetic mean][arithmetic-mean] and [unbiased sample variance][sample-variance].
 
 ```javascript
 var accumulator = incrmeanvar();
 ```
 
 By default, the returned accumulator `function` returns the accumulated values as a two-element `array`. To avoid unnecessary memory allocation, the function supports providing an output (destination) object.
 
 ```javascript
 var Float64Array = require( '@stdlib/array/float64' );
 
 var accumulator = incrmeanvar( new Float64Array( 2 ) );
 ```
 
 #### accumulator( \[x] )
 
 If provided an input value `x`, the accumulator function returns updated accumulated values. If not provided an input value `x`, the accumulator function returns the current accumulated values.
 
 ```javascript
 var accumulator = incrmeanvar();
 
 var mv = accumulator();
 // returns null
 
 mv = accumulator( 2.0 );
 // returns [ 2.0, 0.0 ]
 
 mv = accumulator( 1.0 );
 // returns [ 1.5, 0.5 ]
 
 mv = accumulator( 3.0 );
 // returns [ 2.0, 1.0 ]
 
 mv = accumulator( -7.0 );
 // returns [ -0.25, ~20.92 ]
 
 mv = accumulator( -5.0 );
 // returns [ -1.2, 20.2 ]
 
 mv = accumulator();
 // returns [ -1.2, 20.2 ]
 ```
 
 </section>
 
 <!-- /.usage -->
 
 <section class="notes">
 
 ## Notes
 
 -   Input values are **not** type checked. If provided `NaN`, the accumulated values are equal to `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.
 
 </section>
 
 <!-- /.notes -->
 
 <section class="examples">
 
 ## Examples
 
 <!-- eslint no-undef: "error" -->
 
 ```javascript
 var randu = require( '@stdlib/random/base/randu' );
 var Float64Array = require( '@stdlib/array/float64' );
 var ArrayBuffer = require( '@stdlib/array/buffer' );
 var incrmeanvar = require( '@stdlib/stats/incr/meanvar' );
 
 var offset;
 var acc;
 var buf;
 var out;
 var mv;
 var N;
 var v;
 var i;
 var j;
 
 // Define the number of accumulators:
 N = 5;
 
 // Create an array buffer for storing accumulator output:
 buf = new ArrayBuffer( N*2*8 ); // 8 bytes per element
 
 // Initialize accumulators:
 acc = [];
 for ( i = 0; i < N; i++ ) {
     // Compute the byte offset:
     offset = i * 2 * 8; // stride=2, bytes_per_element=8
 
     // Create a new view for storing accumulated values:
     out = new Float64Array( buf, offset, 2 );
 
     // Initialize an accumulator which will write results to the view:
     acc.push( incrmeanvar( out ) );
 }
 
 // Simulate data and update the sample means and variances...
 for ( i = 0; i < 100; i++ ) {
     for ( j = 0; j < N; j++ ) {
         v = randu() * 100.0 * (j+1);
         acc[ j ]( v );
     }
 }
 
 // Print the final results:
 console.log( 'Mean\tVariance' );
 for ( i = 0; i < N; i++ ) {
     mv = acc[ i ]();
     console.log( '%d\t%d', mv[ 0 ].toFixed( 3 ), mv[ 1 ].toFixed( 3 ) );
 }
 ```
 
 </section>
 
 <!-- /.examples -->
 
 <section class="links">
 
 [arithmetic-mean]: https://en.wikipedia.org/wiki/Arithmetic_mean
 
 [sample-variance]: https://en.wikipedia.org/wiki/Variance
 
 </section>
 
 <!-- /.links -->