smeanpn

Compute the arithmetic mean of a one-dimensional single-precision floating-point ndarray using a two-pass error correction algorithm.

The arithmetic mean is defined as

Installation

npm install @stdlib/stats-base-ndarray-smeanpn

Usage

var smeanpn = require( '@stdlib/stats-base-ndarray-smeanpn' );

smeanpn( arrays )

Computes the arithmetic mean of a one-dimensional single-precision floating-point ndarray using a two-pass error correction algorithm.

var Float32Array = require( '@stdlib/array-float32' );
var ndarray = require( '@stdlib/ndarray-base-ctor' );

var xbuf = new Float32Array( [ 1.0, 3.0, 4.0, 2.0 ] );
var x = new ndarray( 'float32', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );

var v = smeanpn( [ x ] );
// returns 2.5

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

var discreteUniform = require( '@stdlib/random-array-discrete-uniform' );
var ndarray = require( '@stdlib/ndarray-base-ctor' );
var ndarray2array = require( '@stdlib/ndarray-to-array' );
var smeanpn = require( '@stdlib/stats-base-ndarray-smeanpn' );

var xbuf = discreteUniform( 10, -50, 50, {
    'dtype': 'float32'
});
var x = new ndarray( 'float32', xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' );
console.log( ndarray2array( x ) );

var v = smeanpn( [ 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.
• 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.

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

License

See LICENSE.

Copyright

Copyright © 2016-2026. The Stdlib Authors.