README.md

snanmeanors

Compute the arithmetic mean of a one-dimensional single-precision floating-point ndarray, ignoring NaN values and using ordinary recursive summation.

The arithmetic mean is defined as

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

Usage

var snanmeanors = require( '@stdlib/stats/base/ndarray/snanmeanors' );

snanmeanors( arrays )

Computes the arithmetic mean of a one-dimensional single-precision floating-point ndarray, ignoring NaN values and using ordinary recursive summation.

var Float32Array = require( '@stdlib/array/float32' );
var ndarray = require( '@stdlib/ndarray/base/ctor' );

var xbuf = new Float32Array( [ 1.0, 3.0, NaN, 2.0 ] );
var x = new ndarray( 'float32', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );

var v = snanmeanors( [ x ] );
// returns 2.0

The function has the following parameters:

• arrays: array-like object containing a one-dimensional input ndarray.

Notes

• If provided an empty one-dimensional ndarray, the function returns NaN.
• Ordinary recursive summation (i.e., a "simple" sum) is performant, but can incur significant numerical error. If performance is paramount and error tolerated, using ordinary recursive summation to compute an arithmetic mean is acceptable; in all other cases, exercise due caution.

Examples

var uniform = require( '@stdlib/random/base/uniform' );
var filledarrayBy = require( '@stdlib/array/filled-by' );
var bernoulli = require( '@stdlib/random/base/bernoulli' );
var ndarray = require( '@stdlib/ndarray/base/ctor' );
var ndarray2array = require( '@stdlib/ndarray/to-array' );
var snanmeanors = require( '@stdlib/stats/base/ndarray/snanmeanors' );

function rand() {
    if ( bernoulli( 0.8 ) < 1 ) {
        return NaN;
    }
    return uniform( -50.0, 50.0 );
}

var xbuf = filledarrayBy( 10, 'float32', rand );
var x = new ndarray( 'float32', xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' );
console.log( ndarray2array( x ) );

var v = snanmeanors( [ x ] );
console.log( v );