README.md

dmeankbn

Compute the arithmetic mean of a one-dimensional double-precision floating-point ndarray using an improved Kahan–Babuška algorithm.

The arithmetic mean is defined as

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

Usage

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

dmeankbn( arrays )

Computes the arithmetic mean of a one-dimensional double-precision floating-point ndarray using an improved Kahan–Babuška algorithm.

var Float64Array = require( '@stdlib/array/float64' );
var ndarray = require( '@stdlib/ndarray/base/ctor' );

var xbuf = new Float64Array( [ 1.0, 3.0, 4.0, 2.0 ] );
var x = new ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );

var v = dmeankbn( [ x ] );
// returns ~2.5

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.

Examples

var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
var ndarray = require( '@stdlib/ndarray/base/ctor' );
var ndarray2array = require( '@stdlib/ndarray/to-array' );
var dmeankbn = require( '@stdlib/stats/base/ndarray/dmeankbn' );

var xbuf = discreteUniform( 10, -50, 50, {
    'dtype': 'float64'
});
var x = new ndarray( 'float64', xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' );
console.log( ndarray2array( x ) );

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

---

C APIs

Usage

#include "stdlib/stats/base/ndarray/dmeankbn.h"

stdlib_stats_dmeankbn( arrays )

Computes the arithmetic mean of a one-dimensional double-precision floating-point ndarray using an improved Kahan–Babuška algorithm.

#include "stdlib/ndarray/ctor.h"
#include "stdlib/ndarray/dtypes.h"
#include "stdlib/ndarray/index_modes.h"
#include "stdlib/ndarray/orders.h"
#include "stdlib/ndarray/base/bytes_per_element.h"
#include <stdint.h>

// Create an ndarray:
const double data[] = { 1.0, 2.0, 3.0, 4.0 };
int64_t shape[] = { 4 };
int64_t strides[] = { STDLIB_NDARRAY_FLOAT64_BYTES_PER_ELEMENT };
int8_t submodes[] = { STDLIB_NDARRAY_INDEX_ERROR };

struct ndarray *x = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT64, (uint8_t *)data, 1, shape, strides, 0, STDLIB_NDARRAY_ROW_MAJOR, STDLIB_NDARRAY_INDEX_ERROR, 1, submodes );

// Compute the mean value:
const struct ndarray *arrays[] = { x };
double v = stdlib_stats_dmeankbn( arrays );
// returns ~2.5

// Free allocated memory:
stdlib_ndarray_free( x );

The function accepts the following arguments:

• arrays: [in] struct ndarray** list containing a one-dimensional input ndarray.

double stdlib_stats_dmeankbn( const struct ndarray *arrays[] );

Examples

#include "stdlib/stats/base/ndarray/dmeankbn.h"
#include "stdlib/ndarray/ctor.h"
#include "stdlib/ndarray/dtypes.h"
#include "stdlib/ndarray/index_modes.h"
#include "stdlib/ndarray/orders.h"
#include "stdlib/ndarray/base/bytes_per_element.h"
#include <stdint.h>
#include <stdlib.h>
#include <stdio.h>

int main( void ) {
   // Create a data buffer:
   const double data[] = { 1.0, -2.0, 3.0, -4.0, 5.0, -6.0, 7.0, -8.0 };

   // Specify the number of array dimensions:
   const int64_t ndims = 1;

   // Specify the array shape:
   int64_t shape[] = { 4 };

   // Specify the array strides:
   int64_t strides[] = { 2*STDLIB_NDARRAY_FLOAT64_BYTES_PER_ELEMENT };

   // Specify the byte offset:
   const int64_t offset = 0;

   // Specify the array order:
   const enum STDLIB_NDARRAY_ORDER order = STDLIB_NDARRAY_ROW_MAJOR;

   // Specify the index mode:
   const enum STDLIB_NDARRAY_INDEX_MODE imode = STDLIB_NDARRAY_INDEX_ERROR;

   // Specify the subscript index modes:
   int8_t submodes[] = { STDLIB_NDARRAY_INDEX_ERROR };
   const int64_t nsubmodes = 1;

   // Create an ndarray:
   struct ndarray *x = stdlib_ndarray_allocate( STDLIB_NDARRAY_FLOAT64, (uint8_t *)data, ndims, shape, strides, offset, order, imode, nsubmodes, submodes );
   if ( x == NULL ) {
      fprintf( stderr, "Error allocating memory.\n" );
      exit( 1 );
   }

   // Define a list of ndarrays:
   const struct ndarray *arrays[] = { x };

   // Compute the mean value:
   double v = stdlib_stats_dmeankbn( arrays );

   // Print the result:
   printf( "mean: %lf\n", v );

   // Free allocated memory:
   stdlib_ndarray_free( x );
}

References

• Neumaier, Arnold. 1974. "Rounding Error Analysis of Some Methods for Summing Finite Sums." Zeitschrift Für Angewandte Mathematik Und Mechanik 54 (1): 39–51. doi:10.1002/zamm.19740540106.