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incrsummary

Compute a statistical summary incrementally.

Installation

npm install @stdlib/stats-incr-summary

Alternatively,

• To load the package in a website via a script tag without installation and bundlers, use the ES Module available on the esm branch (see README).
• If you are using Deno, visit the deno branch (see README for usage intructions).
• For use in Observable, or in browser/node environments, use the Universal Module Definition (UMD) build available on the umd branch (see README).

The branches.md file summarizes the available branches and displays a diagram illustrating their relationships.

To view installation and usage instructions specific to each branch build, be sure to explicitly navigate to the respective README files on each branch, as linked to above.

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() );

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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.

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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

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License

See LICENSE.

Copyright

Copyright © 2016-2024. The Stdlib Authors.