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    @stdlib/stats-base-dnanmean
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    0.0.9 • Public • Published

    dnanmean

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    Calculate the arithmetic mean of a double-precision floating-point strided array, ignoring NaN values.

    The arithmetic mean is defined as

    Equation for the arithmetic mean.

    Installation

    npm install @stdlib/stats-base-dnanmean

    Usage

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

    dnanmean( N, x, stride )

    Computes the arithmetic mean of a double-precision floating-point strided array x, ignoring NaN values.

    var Float64Array = require( '@stdlib/array-float64' );
    
    var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );
    var N = x.length;
    
    var v = dnanmean( N, x, 1 );
    // returns ~0.3333

    The function has the following parameters:

    • N: number of indexed elements.
    • x: input Float64Array.
    • 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 Float64Array = require( '@stdlib/array-float64' );
    var floor = require( '@stdlib/math-base-special-floor' );
    
    var x = new Float64Array( [ 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 = dnanmean( 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, NaN ] );
    var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
    
    var N = floor( x0.length / 2 );
    
    var v = dnanmean( N, x1, 2 );
    // returns 1.25

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

    Computes the arithmetic mean of a double-precision floating-point strided array, ignoring NaN values and using alternative indexing semantics.

    var Float64Array = require( '@stdlib/array-float64' );
    
    var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );
    var N = x.length;
    
    var v = dnanmean.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 Float64Array = require( '@stdlib/array-float64' );
    var floor = require( '@stdlib/math-base-special-floor' );
    
    var x = new Float64Array( [ 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 = dnanmean.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

    var randu = require( '@stdlib/random-base-randu' );
    var round = require( '@stdlib/math-base-special-round' );
    var Float64Array = require( '@stdlib/array-float64' );
    var dnanmean = require( '@stdlib/stats-base-dnanmean' );
    
    var x;
    var i;
    
    x = new Float64Array( 10 );
    for ( i = 0; i < x.length; i++ ) {
        if ( randu() < 0.2 ) {
            x[ i ] = NaN;
        } else {
            x[ i ] = round( randu() * 10.0 );
        }
    }
    console.log( x );
    
    var v = dnanmean( x.length, x, 1 );
    console.log( v );

    See Also


    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.

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    License

    See LICENSE.

    Copyright

    Copyright © 2016-2022. The Stdlib Authors.

    Install

    npm i @stdlib/stats-base-dnanmean

    Homepage

    stdlib.io

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    30

    Version

    0.0.9

    License

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    Unpacked Size

    57.3 kB

    Total Files

    20

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    Collaborators

    • stdlib-bot
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