Calculate the arithmetic mean of a strided array using a two-pass error correction algorithm.
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> Calculate the [arithmetic mean][arithmetic-mean] of a strided array using a two-pass error correction algorithm.
The [arithmetic mean][arithmetic-mean] is defined as
``bash`
npm install @stdlib/stats-strided-meanpn
`javascript`
var meanpn = require( '@stdlib/stats-strided-meanpn' );
#### meanpn( N, x, strideX )
Computes the [arithmetic mean][arithmetic-mean] of a strided array using a two-pass error correction algorithm.
`javascript
var x = [ 1.0, -2.0, 2.0 ];
var v = meanpn( x.length, x, 1 );
// returns ~0.3333
`
The function has the following parameters:
- N: number of indexed elements.
- x: input [Array][mdn-array] or [typed array][mdn-typed-array].x
- strideX: stride length for .
The N and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the [arithmetic mean][arithmetic-mean] of every other element in the input array
`javascript`
var x = [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ];
var v = meanpn( 4, x, 2 );
// returns 1.25
Note that indexing is relative to the first index. To introduce an offset, use [typed array][mdn-typed-array] views.
`javascript
var Float64Array = require( '@stdlib/array-float64' );
var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
var v = meanpn( 4, x1, 2 );
// returns 1.25
`
#### meanpn.ndarray( N, x, strideX, offsetX )
Computes the [arithmetic mean][arithmetic-mean] of a strided array using a two-pass error correction algorithm and alternative indexing semantics.
`javascript
var x = [ 1.0, -2.0, 2.0 ];
var v = meanpn.ndarray( x.length, x, 1, 0 );
// returns ~0.33333
`
The function has the following additional parameters:
- offsetX: starting index for x.
While [typed array][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the [arithmetic mean][arithmetic-mean] for every other element in the strided array starting from the second element
`javascript
var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ];
var v = meanpn.ndarray( 4, x, 2, 1 );
// returns 1.25
`
- If N <= 0, both functions return NaN.@stdlib/array-base/accessor
- Both functions support array-like objects having getter and setter accessors for array element access (e.g., [][@stdlib/array/base/accessor]).dmeanpn
- Depending on the environment, the typed versions ([][@stdlib/stats/strided/dmeanpn], [smeanpn][@stdlib/stats/strided/smeanpn], etc.) are likely to be significantly more performant.
`javascript
var discreteUniform = require( '@stdlib/random-array-discrete-uniform' );
var meanpn = require( '@stdlib/stats-strided-meanpn' );
var x = discreteUniform( 10, -50, 50, {
'dtype': 'float64'
});
console.log( x );
var v = meanpn( x.length, x, 1 );
console.log( v );
`
*
- 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].
*
- [@stdlib/stats-strided/dmeanpn][@stdlib/stats/strided/dmeanpn]: calculate the arithmetic mean of a double-precision floating-point strided array using a two-pass error correction algorithm.
- [@stdlib/stats-strided/mean][@stdlib/stats/strided/mean]: calculate the arithmetic mean of a strided array.
- [@stdlib/stats-strided/nanmeanpn][@stdlib/stats/strided/nanmeanpn]: calculate the arithmetic mean of a strided array, ignoring NaN values and using a two-pass error correction algorithm.
- [@stdlib/stats-strided/smeanpn][@stdlib/stats/strided/smeanpn]: calculate the arithmetic mean of a single-precision floating-point strided array using a two-pass error correction algorithm.
*
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].
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[arithmetic-mean]: https://en.wikipedia.org/wiki/Arithmetic_mean
[mdn-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Array
[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray
[@stdlib/array/base/accessor]: https://www.npmjs.com/package/@stdlib/array-base-accessor
[@neely:1966a]: https://doi.org/10.1145/365719.365958
[@schubert:2018a]: https://doi.org/10.1145/3221269.3223036
[@stdlib/stats/strided/dmeanpn]: https://www.npmjs.com/package/@stdlib/stats-strided-dmeanpn
[@stdlib/stats/strided/mean]: https://www.npmjs.com/package/@stdlib/stats-strided-mean
[@stdlib/stats/strided/nanmeanpn]: https://www.npmjs.com/package/@stdlib/stats-strided-nanmeanpn
[@stdlib/stats/strided/smeanpn]: https://www.npmjs.com/package/@stdlib/stats-strided-smeanpn