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@stdlib/stats-base-mean
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Calculate the arithmetic mean of a strided array.
The arithmetic mean is defined as
npm install @stdlib/stats-base-mean
var mean = require( '@stdlib/stats-base-mean' );
Computes the arithmetic mean of a strided array x
.
var x = [ 1.0, -2.0, 2.0 ];
var N = x.length;
var v = mean( N, x, 1 );
// returns ~0.3333
The function has the following parameters:
Array
or typed array
.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
,
var floor = require( '@stdlib/math-base-special-floor' );
var x = [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ];
var N = floor( x.length / 2 );
var v = mean( N, x, 2 );
// returns 1.25
Note that indexing is relative to the first index. To introduce an offset, use typed array
views.
var Float64Array = require( '@stdlib/array-float64' );
var floor = require( '@stdlib/math-base-special-floor' );
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 N = floor( x0.length / 2 );
var v = mean( N, x1, 2 );
// returns 1.25
Computes the arithmetic mean of a strided array using alternative indexing semantics.
var x = [ 1.0, -2.0, 2.0 ];
var N = x.length;
var v = mean.ndarray( N, x, 1, 0 );
// returns ~0.33333
The function has the following additional parameters:
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
var floor = require( '@stdlib/math-base-special-floor' );
var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ];
var N = floor( x.length / 2 );
var v = mean.ndarray( N, x, 2, 1 );
// returns 1.25
var randu = require( '@stdlib/random-base-randu' );
var round = require( '@stdlib/math-base-special-round' );
var Float64Array = require( '@stdlib/array-float64' );
var mean = require( '@stdlib/stats-base-mean' );
var x;
var i;
x = new Float64Array( 10 );
for ( i = 0; i < x.length; i++ ) {
x[ i ] = round( (randu()*100.0) - 50.0 );
}
console.log( x );
var v = mean( x.length, x, 1 );
console.log( v );
@stdlib/stats-base/dmean
: calculate the arithmetic mean of a double-precision floating-point strided array.@stdlib/stats-base/nanmean
: calculate the arithmetic mean of a strided array, ignoring NaN values.@stdlib/stats-base/smean
: calculate the arithmetic mean of a single-precision floating-point strided array.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.
See LICENSE.
Copyright © 2016-2024. The Stdlib Authors.
0.2.2 (2024-07-28)
No changes reported for this release.
</section> <!-- /.release --> <section class="release" id="v0.2.1">FAQs
Calculate the arithmetic mean of a strided array.
The npm package @stdlib/stats-base-mean receives a total of 18,994 weekly downloads. As such, @stdlib/stats-base-mean popularity was classified as popular.
We found that @stdlib/stats-base-mean demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 0 open source maintainers collaborating on the project.
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