@stdlib/stats-incr-mmaape

Compute a moving arctangent mean absolute percentage error (MAAPE) incrementally.

https://github.com/stdlib-js/stats-incr-mmaape

Science Score: 67.0%

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Keywords

abs absolute accumulator average avg err error incremental javascript maape mape math mathematics mean node node-js nodejs statistics stats stdlib

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Compute a moving arctangent mean absolute percentage error (MAAPE) incrementally.

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Host: GitHub
Owner: stdlib-js
License: apache-2.0
Language: JavaScript
Default Branch: main
Homepage: https://github.com/stdlib-js/stdlib
Size: 952 KB

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abs absolute accumulator average avg err error incremental javascript maape mape math mathematics mean node node-js nodejs statistics stats stdlib

Created over 4 years ago · Last pushed 5 months ago

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Readme Changelog Contributing License Code of conduct Citation Security

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!

incrmmaape

Compute a moving mean arctangent absolute percentage error (MAAPE) incrementally.

For a window of size `W`, the [mean arctangent absolute percentage error][@kim:2016a] is defined as ```math \mathop{\mathrm{MAAPE}} = \frac{1}{W} \sum_{i=0}^{W-1} \mathop{\mathrm{arctan}}\biggl( \biggl| \frac{a_i - f_i}{a_i} \biggr| \biggr) ``` where `f_i` is the forecast value and `a_i` is the actual value.

## Installation ```bash npm install @stdlib/stats-incr-mmaape ``` Alternatively, - To load the package in a website via a `script` tag without installation and bundlers, use the [ES Module][es-module] available on the [`esm`][esm-url] branch (see [README][esm-readme]). - If you are using Deno, visit the [`deno`][deno-url] branch (see [README][deno-readme] for usage intructions). - For use in Observable, or in browser/node environments, use the [Universal Module Definition (UMD)][umd] build available on the [`umd`][umd-url] branch (see [README][umd-readme]). The [branches.md][branches-url] 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 ```javascript var incrmmaape = require( '@stdlib/stats-incr-mmaape' ); ``` #### incrmmaape( window ) Returns an accumulator `function` which incrementally computes a moving [mean arctangent absolute percentage error][@kim:2016a]. The `window` parameter defines the number of values over which to compute the moving [mean arctangent absolute percentage error][@kim:2016a]. ```javascript var accumulator = incrmmaape( 3 ); ``` #### accumulator( \[f, a] ) If provided input values `f` and `a`, the accumulator function returns an updated [mean arctangent absolute percentage error][@kim:2016a]. If not provided input values `f` and `a`, the accumulator function returns the current [mean arctangent absolute percentage error][@kim:2016a]. ```javascript var accumulator = incrmmaape( 3 ); var m = accumulator(); // returns null // Fill the window... m = accumulator( 2.0, 3.0 ); // [(2.0,3.0)] // returns ~0.32 m = accumulator( 1.0, 4.0 ); // [(2.0,3.0), (1.0,4.0)] // returns ~0.48 m = accumulator( 3.0, 9.0 ); // [(2.0,3.0), (1.0,4.0), (3.0,9.0)] // returns ~0.52 // Window begins sliding... m = accumulator( 7.0, 3.0 ); // [(1.0,4.0), (3.0,9.0), (7.0,3.0)] // returns ~0.72 m = accumulator( 5.0, 3.0 ); // [(3.0,9.0), (7.0,3.0), (5.0,3.0)] // returns ~0.70 m = accumulator(); // returns ~0.70 ```

## 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` (f,a) 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. - Note that, unlike the [mean absolute percentage error][@stdlib/stats/incr/mape] (MAPE), the [mean arctangent absolute percentage error][@kim:2016a] is expressed in radians on the interval \[0,π/2].

## Examples ```javascript var randu = require( '@stdlib/random-base-randu' ); var incrmmaape = require( '@stdlib/stats-incr-mmaape' ); var accumulator; var v1; var v2; var i; // Initialize an accumulator: accumulator = incrmmaape( 5 ); // For each simulated datum, update the moving mean arctangent absolute percentage 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() ); ```

## References - Kim, Sungil, and Heeyoung Kim. 2016. "A new metric of absolute percentage error for intermittent demand forecasts." _International Journal of Forecasting_ 32 (3): 669–79. doi:[10.1016/j.ijforecast.2015.12.003][@kim:2016a].

* * * ## Notice This package is part of [stdlib][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][stdlib], see the main project [repository][stdlib]. #### Community [![Chat][chat-image]][chat-url] --- ## License See [LICENSE][stdlib-license]. ## Copyright Copyright © 2016-2025. The Stdlib [Authors][stdlib-authors].

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Twitter: stdlibjs
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Standard library for JavaScript.

Citation (CITATION.cff)

cff-version: 1.2.0
title: stdlib
message: >-
  If you use this software, please cite it using the
  metadata from this file.

type: software

authors:
  - name: The Stdlib Authors
    url: https://github.com/stdlib-js/stdlib/graphs/contributors

repository-code: https://github.com/stdlib-js/stdlib
url: https://stdlib.io

abstract: |
  Standard library for JavaScript and Node.js.

keywords:
  - JavaScript
  - Node.js
  - TypeScript
  - standard library
  - scientific computing
  - numerical computing
  - statistical computing

license: Apache-2.0 AND BSL-1.0

date-released: 2016

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npmjs.org: @stdlib/stats-incr-mmaape

Compute a moving arctangent mean absolute percentage error (MAAPE) incrementally.

Homepage: https://stdlib.io
License: Apache-2.0
Latest release: 0.2.2
published over 1 year ago

Versions: 11
Dependent Packages: 3
Dependent Repositories: 3
Downloads: 80 Last month

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Dependent packages count: 5.9%

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Average: 11.1%

Downloads: 13.2%

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planeshifter rreusser stdlib-bot kgryte

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package.json npm

@stdlib/bench ^0.0.x development
@stdlib/constants-float64-eps ^0.0.x development
@stdlib/math-base-assert-is-nan ^0.0.x development
@stdlib/random-base-randu ^0.0.x development
istanbul ^0.4.1 development
tap-spec 5.x.x development
tape git+https://github.com/kgryte/tape.git#fix/globby development
@stdlib/assert-is-positive-integer ^0.0.x
@stdlib/math-base-special-abs ^0.0.x
@stdlib/math-base-special-atan ^0.0.x
@stdlib/stats-incr-mmean ^0.0.x
@stdlib/string-format ^0.0.x
@stdlib/types ^0.0.x

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@stdlib/stats-incr-mmaape

Science Score: 67.0%

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