@stdlib/stats-base-ndarray-snanmeanpn
v0.1.1TypeScript
Compute the arithmetic mean of a one-dimensional single-precision floating-point ndarray, ignoring `NaN` values and using a two-pass error correction algorithm.
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Published by The Stdlib Authors
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snanmeanpn
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> Compute the [arithmetic mean][arithmetic-mean] of a one-dimensional single-precision floating-point ndarray, ignoring NaN values and using a two-pass error correction algorithm.
The [arithmetic mean][arithmetic-mean] is defined as
Installation
``bash`
npm install @stdlib/stats-base-ndarray-snanmeanpn
Usage
`javascript`
var snanmeanpn = require( '@stdlib/stats-base-ndarray-snanmeanpn' );
#### snanmeanpn( arrays )
Computes the [arithmetic mean][arithmetic-mean] of a one-dimensional single-precision floating-point ndarray, ignoring NaN values and using a two-pass error correction algorithm.
`javascript
var Float32Array = require( '@stdlib/array-float32' );
var ndarray = require( '@stdlib/ndarray-base-ctor' );
var xbuf = new Float32Array( [ 1.0, 3.0, NaN, 2.0 ] );
var x = new ndarray( 'float32', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
var v = snanmeanpn( [ x ] );
// returns 2.0
`
The function has the following parameters:
- arrays: array-like object containing a one-dimensional input ndarray.
Notes
- If provided an empty one-dimensional ndarray, the function returns NaN.
Examples
`javascript
var uniform = require( '@stdlib/random-base-uniform' );
var filledarrayBy = require( '@stdlib/array-filled-by' );
var bernoulli = require( '@stdlib/random-base-bernoulli' );
var ndarray = require( '@stdlib/ndarray-base-ctor' );
var ndarray2array = require( '@stdlib/ndarray-to-array' );
var snanmeanpn = require( '@stdlib/stats-base-ndarray-snanmeanpn' );
function rand() {
if ( bernoulli( 0.8 ) < 1 ) {
return NaN;
}
return uniform( -50.0, 50.0 );
}
var xbuf = filledarrayBy( 10, 'float32', rand );
var x = new ndarray( 'float32', xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' );
console.log( ndarray2array( x ) );
var v = snanmeanpn( [ x ] );
console.log( v );
`
*
References
- Neely, Peter M. 1966. "Comparison of Several Algorithms for Computation of Means, Standard Deviations and Correlation Coefficients." _Communications of the ACM_ 9 (7). Association for Computing Machinery: 496–99. doi:[10.1145/365719.365958][@neely:1966a].
- Schubert, Erich, and Michael Gertz. 2018. "Numerically Stable Parallel Computation of (Co-)Variance." In _Proceedings of the 30th International Conference on Scientific and Statistical Database Management_. New York, NY, USA: Association for Computing Machinery. doi:[10.1145/3221269.3223036][@schubert:2018a].
*
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 © 2016-2026. The Stdlib [Authors][stdlib-authors].
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[umd]: https://github.com/umdjs/umd
[es-module]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Guide/Modules
[deno-url]: https://github.com/stdlib-js/stats-base-ndarray-snanmeanpn/tree/deno
[deno-readme]: https://github.com/stdlib-js/stats-base-ndarray-snanmeanpn/blob/deno/README.md
[umd-url]: https://github.com/stdlib-js/stats-base-ndarray-snanmeanpn/tree/umd
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[esm-url]: https://github.com/stdlib-js/stats-base-ndarray-snanmeanpn/tree/esm
[esm-readme]: https://github.com/stdlib-js/stats-base-ndarray-snanmeanpn/blob/esm/README.md
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[stdlib-license]: https://raw.githubusercontent.com/stdlib-js/stats-base-ndarray-snanmeanpn/main/LICENSE
[arithmetic-mean]: https://en.wikipedia.org/wiki/Arithmetic_mean
[@neely:1966a]: https://doi.org/10.1145/365719.365958
[@schubert:2018a]: https://doi.org/10.1145/3221269.3223036