@stdlib/stats-incr-summary

About stdlib...

We believe in a future in which the web is a preferred environment for numerical computation. To help realize this future, we've built stdlib. stdlib is a standard library, with an emphasis on numerical and scientific computation, written in JavaScript (and C) for execution in browsers and in Node.js.

The library is fully decomposable, being architected in such a way that you can swap out and mix and match APIs and functionality to cater to your exact preferences and use cases.

When you use stdlib, you can be absolutely certain that you are using the most thorough, rigorous, well-written, studied, documented, tested, measured, and high-quality code out there.

To join us in bringing numerical computing to the web, get started by checking us out on GitHub, and please consider financially supporting stdlib. We greatly appreciate your continued support!

incrsummary

Compute a statistical summary incrementally.

Installation

npm install @stdlib/stats-incr-summary

Usage

var incrsummary = require( '@stdlib/stats-incr-summary' );

incrsummary()

Returns an accumulator function which incrementally computes a statistical summary.

var accumulator = incrsummary();

accumulator( [x] )

If provided an input value x, the accumulator function returns an updated summary. If not provided an input value x, the accumulator function returns the current summary.

var accumulator = incrsummary();

var summary = accumulator();
// returns {}

summary = accumulator( 2.0 );
/* returns
    {
        'count': 1,
        'max': 2.0,
        'min': 2.0,
        'range': 0.0,
        'midrange': 2.0,
        'sum': 2.0,
        'mean': 2.0,
        'variance': 0.0,
        'stdev': 0.0,
        'skewness': null,
        'kurtosis': null
    }
*/

summary = accumulator( 1.0 );
/* returns
    {
        'count': 2,
        'max': 2.0,
        'min': 1.0,
        'range': 1.0,
        'midrange': 1.5,
        'sum': 3.0,
        'mean': 1.5,
        'variance': 0.5,
        'stdev': 0.7071067811865476,
        'skewness': null,
        'kurtosis': null
    }
*/

summary = accumulator( -3.0 );
/* returns
    {
        'count': 3,
        'max': 2.0,
        'min': -3.0,
        'range': 5.0,
        'midrange': -0.5,
        'sum': 0.0,
        'mean': 0.0,
        'variance': 7,
        'stdev': ~2.65,
        'skewness': ~-1.46,
        'kurtosis': null
    }
*/

summary = accumulator();
/* returns
    {
        'count': 3,
        'max': 2.0,
        'min': -3.0,
        'range': 5.0,
        'midrange': -0.5,
        'sum': 0.0,
        'mean': 0.0,
        'variance': 7,
        'stdev': ~2.65,
        'skewness': ~-1.46,
        'kurtosis': null
    }
*/

Notes

• Input values are not type checked. If non-numeric inputs are possible, you are advised to type check and handle accordingly before passing the value to the accumulator function.
• For long running accumulations or accumulations of large numbers, care should be taken to prevent overflow.

Examples

var randu = require( '@stdlib/random-base-randu' );
var incrsummary = require( '@stdlib/stats-incr-summary' );

var accumulator;
var v;
var i;

// Initialize an accumulator:
accumulator = incrsummary();

// For each simulated datum, update the summary...
for ( i = 0; i < 100; i++ ) {
    v = randu() * 100.0;
    accumulator( v );
}
console.log( accumulator() );

---

See Also

• @stdlib/stats-incr/count: compute a count incrementally.
• @stdlib/stats-incr/kurtosis: compute a corrected sample excess kurtosis incrementally.
• @stdlib/stats-incr/max: compute a maximum value incrementally.
• @stdlib/stats-incr/mean: compute an arithmetic mean incrementally.
• @stdlib/stats-incr/midrange: compute a mid-range incrementally.
• @stdlib/stats-incr/min: compute a minimum value incrementally.
• @stdlib/stats-incr/msummary: compute a moving statistical summary incrementally.
• @stdlib/stats-incr/range: compute a range incrementally.
• @stdlib/stats-incr/skewness: compute a corrected sample skewness incrementally.
• @stdlib/stats-incr/stdev: compute a corrected sample standard deviation incrementally.
• @stdlib/stats-incr/sum: compute a sum incrementally.
• @stdlib/stats-incr/variance: compute an unbiased sample variance incrementally.

---

Notice

This package is part of stdlib, a standard library for JavaScript and Node.js, with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more.

For more information on the project, filing bug reports and feature requests, and guidance on how to develop stdlib, see the main project repository.

Community

---

License

See LICENSE.

Copyright

Copyright © 2016-2024. The Stdlib Authors.