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@stdlib/stats-incr-mrss

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@stdlib/stats-incr-mrss

Compute a moving residual sum of squares (RSS) incrementally.

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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!

incrmrss

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Compute a moving residual sum of squares (RSS) incrementally.

For a window of size W, the residual sum of squares (also referred to as the sum of squared residuals (SSR) and the sum of squared errors (SSE)) is defined as

Equation for the residual sum of squares.

Installation

npm install @stdlib/stats-incr-mrss

Usage

var incrmrss = require( '@stdlib/stats-incr-mrss' );
incrmrss( window )

Returns an accumulator function which incrementally computes a moving residual sum of squares. The window parameter defines the number of values over which to compute the moving residual sum of squares.

var accumulator = incrmrss( 3 );
accumulator( [x, y] )

If provided input values x and y, the accumulator function returns an updated residual sum of squares. If not provided input values x and y, the accumulator function returns the current residual sum of squares.

var accumulator = incrmrss( 3 );

var r = accumulator();
// returns null

// Fill the window...
r = accumulator( 2.0, 3.0 ); // [(2.0,3.0)]
// returns 1.0

r = accumulator( -1.0, 4.0 ); // [(2.0,3.0), (-1.0,4.0)]
// returns 26.0

r = accumulator( 3.0, 9.0 ); // [(2.0,3.0), (-1.0,4.0), (3.0,9.0)]
// returns 62.0

// Window begins sliding...
r = accumulator( -7.0, 3.0 ); // [(-1.0,4.0), (3.0,9.0), (-7.0,3.0)]
// returns 161.0

r = accumulator( -5.0, -3.0 ); // [(3.0,9.0), (-7.0,3.0), (-5.0,-3.0)]
// returns 140.0

r = accumulator();
// returns 140.0

Notes

  • 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 at least W-1 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.
  • As W (x,y) pairs are needed to fill the window buffer, the first W-1 returned values are calculated from smaller sample sizes. Until the window is full, each returned value is calculated from all provided values.

Examples

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

var accumulator;
var v1;
var v2;
var i;

// Initialize an accumulator:
accumulator = incrmrss( 5 );

// For each simulated datum, update the moving residual sum of squares...
for ( i = 0; i < 100; i++ ) {
    v1 = ( randu()*100.0 ) - 50.0;
    v2 = ( randu()*100.0 ) - 50.0;
    accumulator( v1, v2 );
}
console.log( accumulator() );

See Also


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.

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License

See LICENSE.

Copyright © 2016-2024. The Stdlib Authors.

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Package last updated on 27 Jul 2024

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