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About stdlib...

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snanmeanwd

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Calculate the arithmetic mean of a single-precision floating-point strided array, ignoring NaN values and using Welford's algorithm.

The arithmetic mean is defined as

$$\mu = \frac{1}{n} \sum_{i=0}^{n-1} x_i$$

Usage

import snanmeanwd from 'https://cdn.jsdelivr.net/gh/stdlib-js/stats-base-snanmeanwd@esm/index.mjs';

snanmeanwd( N, x, stride )

Computes the arithmetic mean of a single-precision floating-point strided array x, ignoring NaN values and using Welford's algorithm.

import Float32Array from 'https://cdn.jsdelivr.net/gh/stdlib-js/array-float32@esm/index.mjs';

var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );
var N = x.length;

var v = snanmeanwd( N, x, 1 );
// returns ~0.3333

The function has the following parameters:

  • N: number of indexed elements.
  • x: input Float32Array.
  • stride: index increment for x.

The N and stride parameters determine which elements in x are accessed at runtime. For example, to compute the arithmetic mean of every other element in x,

import Float32Array from 'https://cdn.jsdelivr.net/gh/stdlib-js/array-float32@esm/index.mjs';
import floor from 'https://cdn.jsdelivr.net/gh/stdlib-js/math-base-special-floor@esm/index.mjs';

var x = new Float32Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0, NaN ] );
var N = floor( x.length / 2 );

var v = snanmeanwd( N, x, 2 );
// returns 1.25

Note that indexing is relative to the first index. To introduce an offset, use typed array views.

import Float32Array from 'https://cdn.jsdelivr.net/gh/stdlib-js/array-float32@esm/index.mjs';
import floor from 'https://cdn.jsdelivr.net/gh/stdlib-js/math-base-special-floor@esm/index.mjs';

var x0 = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN ] );
var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element

var N = floor( x0.length / 2 );

var v = snanmeanwd( N, x1, 2 );
// returns 1.25

snanmeanwd.ndarray( N, x, stride, offset )

Computes the arithmetic mean of a single-precision floating-point strided array, ignoring NaN values and using Welford's algorithm and alternative indexing semantics.

import Float32Array from 'https://cdn.jsdelivr.net/gh/stdlib-js/array-float32@esm/index.mjs';

var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );
var N = x.length;

var v = snanmeanwd.ndarray( N, x, 1, 0 );
// returns ~0.33333

The function has the following additional parameters:

  • offset: starting index for x.

While 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 for every other value in x starting from the second value

import Float32Array from 'https://cdn.jsdelivr.net/gh/stdlib-js/array-float32@esm/index.mjs';
import floor from 'https://cdn.jsdelivr.net/gh/stdlib-js/math-base-special-floor@esm/index.mjs';

var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN ] );
var N = floor( x.length / 2 );

var v = snanmeanwd.ndarray( N, x, 2, 1 );
// returns 1.25

Notes

  • If N <= 0, both functions return NaN.
  • If every indexed element is NaN, both functions return NaN.

Examples

<!DOCTYPE html>
<html lang="en">
<body>
<script type="module">

import randu from 'https://cdn.jsdelivr.net/gh/stdlib-js/random-base-randu@esm/index.mjs';
import round from 'https://cdn.jsdelivr.net/gh/stdlib-js/math-base-special-round@esm/index.mjs';
import Float32Array from 'https://cdn.jsdelivr.net/gh/stdlib-js/array-float32@esm/index.mjs';
import snanmeanwd from 'https://cdn.jsdelivr.net/gh/stdlib-js/stats-base-snanmeanwd@esm/index.mjs';

var x;
var i;

x = new Float32Array( 10 );
for ( i = 0; i < x.length; i++ ) {
    if ( randu() < 0.2 ) {
        x[ i ] = NaN;
    } else {
        x[ i ] = round( (randu()*100.0) - 50.0 );
    }
}
console.log( x );

var v = snanmeanwd( x.length, x, 1 );
console.log( v );

</script>
</body>
</html>

References

  • Welford, B. P. 1962. "Note on a Method for Calculating Corrected Sums of Squares and Products." Technometrics 4 (3). Taylor & Francis: 419–20. doi:10.1080/00401706.1962.10490022.
  • van Reeken, A. J. 1968. "Letters to the Editor: Dealing with Neely's Algorithms." Communications of the ACM 11 (3): 149–50. doi:10.1145/362929.362961.

See Also

  • @stdlib/stats-base/dnanmeanwd: calculate the arithmetic mean of a double-precision floating-point strided array, using Welford's algorithm and ignoring NaN values.
  • @stdlib/stats-base/nanmeanwd: calculate the arithmetic mean of a strided array, ignoring NaN values and using Welford's algorithm.
  • @stdlib/stats-base/smeanwd: calculate the arithmetic mean of a single-precision floating-point strided array using Welford's algorithm.
  • @stdlib/stats-base/snanmean: calculate the arithmetic mean of a single-precision floating-point strided array, ignoring NaN values.

Notice

This package is part of stdlib, a standard library 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.

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License

See LICENSE.

Copyright

Copyright © 2016-2024. The Stdlib Authors.