@stdlib/stats-base-mean
v0.2.2
Published
Calculate the arithmetic mean of a strided array.
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mean
Calculate the arithmetic mean of a strided array.
The arithmetic mean is defined as
Installation
npm install @stdlib/stats-base-mean
Usage
var mean = require( '@stdlib/stats-base-mean' );
mean( N, x, stride )
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:
- N: number of indexed elements.
- x: input
Array
ortyped array
. - 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
,
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
mean.ndarray( N, x, stride, offset )
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:
- 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
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
Notes
- If
N <= 0
, both functions returnNaN
. - Depending on the environment, the typed versions (
dmean
,smean
, etc.) are likely to be significantly more performant.
Examples
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 );
See Also
@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.
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 © 2016-2024. The Stdlib Authors.