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Compute a moving root mean squared error (RMSE) incrementally.
For a window of size W
, the root mean squared error (also known as the root mean square error (RMSE) and root mean square deviation (RMSD)) is defined as
npm install @stdlib/stats-incr-mrmse
Alternatively,
- To load the package in a website via a
script
tag without installation and bundlers, use the ES Module available on theesm
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.
var incrmrmse = require( '@stdlib/stats-incr-mrmse' );
Returns an accumulator function
which incrementally computes a moving root mean squared error. The window
parameter defines the number of values over which to compute the moving root mean squared error.
var accumulator = incrmrmse( 3 );
If provided input values x
and y
, the accumulator function returns an updated root mean squared error. If not provided input values x
and y
, the accumulator function returns the current root mean squared error.
var accumulator = incrmrmse( 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 ~3.61
r = accumulator( 3.0, 9.0 ); // [(2.0,3.0), (-1.0,4.0), (3.0,9.0)]
// returns ~4.55
// Window begins sliding...
r = accumulator( -7.0, 3.0 ); // [(-1.0,4.0), (3.0,9.0), (-7.0,3.0)]
// returns ~7.33
r = accumulator( -5.0, -3.0 ); // [(3.0,9.0), (-7.0,3.0), (-5.0,-3.0)]
// returns ~6.83
r = accumulator();
// returns ~6.83
- Input values are not type checked. If provided
NaN
or a value which, when used in computations, results inNaN
, the accumulated value isNaN
for at leastW-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 firstW-1
returned values are calculated from smaller sample sizes. Until the window is full, each returned value is calculated from all provided values.
var randu = require( '@stdlib/random-base-randu' );
var incrmrmse = require( '@stdlib/stats-incr-mrmse' );
var accumulator;
var v1;
var v2;
var i;
// Initialize an accumulator:
accumulator = incrmrmse( 5 );
// For each simulated datum, update the moving root mean squared error...
for ( i = 0; i < 100; i++ ) {
v1 = ( randu()*100.0 ) - 50.0;
v2 = ( randu()*100.0 ) - 50.0;
accumulator( v1, v2 );
}
console.log( accumulator() );
@stdlib/stats-incr/mmse
: compute a moving mean squared error (MSE) incrementally.@stdlib/stats-incr/mrss
: compute a moving residual sum of squares (RSS) incrementally.@stdlib/stats-incr/rmse
: compute the root mean squared error (RMSE) incrementally.
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.
See LICENSE.
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