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Calculate the arithmetic mean of a single-precision floating-point strided array using a two-pass error correction algorithm with extended accumulation and returning an extended precision result.
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stdlib-js/stats-base-dsmeanpn
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Calculate thearithmetic mean of a single-precision floating-point strided array using a two-pass error correction algorithm with extended accumulation and returning an extended precision result.
Thearithmetic mean is defined as
npm install @stdlib/stats-base-dsmeanpn
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vardsmeanpn=require('@stdlib/stats-base-dsmeanpn');
Computes thearithmetic mean of a single-precision floating-point strided arrayx using a two-pass error correction algorithm with extended accumulation and returning an extended precision result.
varFloat32Array=require('@stdlib/array-float32');varx=newFloat32Array([1.0,-2.0,2.0]);varv=dsmeanpn(x.length,x,1);// returns ~0.3333
The function has the following parameters:
- N: number of indexed elements.
- x: input
Float32Array. - strideX: stride length for
x.
TheN and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute thearithmetic mean of every other element inx,
varFloat32Array=require('@stdlib/array-float32');varx=newFloat32Array([1.0,2.0,2.0,-7.0,-2.0,3.0,4.0,2.0]);varv=dsmeanpn(4,x,2);// returns 1.25
Note that indexing is relative to the first index. To introduce an offset, usetyped array views.
varFloat32Array=require('@stdlib/array-float32');varx0=newFloat32Array([2.0,1.0,2.0,-2.0,-2.0,2.0,3.0,4.0]);varx1=newFloat32Array(x0.buffer,x0.BYTES_PER_ELEMENT*1);// start at 2nd elementvarv=dsmeanpn(4,x1,2);// returns 1.25
Computes thearithmetic mean of a single-precision floating-point strided array using a two-pass error correction algorithm with extended accumulation and alternative indexing semantics and returning an extended precision result.
varFloat32Array=require('@stdlib/array-float32');varx=newFloat32Array([1.0,-2.0,2.0]);varv=dsmeanpn.ndarray(x.length,x,1,0);// returns ~0.33333
The function has the following additional parameters:
- offsetX: starting index for
x.
Whiletyped 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 thearithmetic mean for every other element inx starting from the second element
varFloat32Array=require('@stdlib/array-float32');varx=newFloat32Array([2.0,1.0,2.0,-2.0,-2.0,2.0,3.0,4.0]);varv=dsmeanpn.ndarray(4,x,2,1);// returns 1.25
- If
N <= 0, both functions returnNaN. - Accumulated intermediate values are stored as double-precision floating-point numbers.
vardiscreteUniform=require('@stdlib/random-array-discrete-uniform');vardsmeanpn=require('@stdlib/stats-base-dsmeanpn');varx=discreteUniform(10,-50,50,{'dtype':'float32'});console.log(x);varv=dsmeanpn(x.length,x,1);console.log(v);
#include"stdlib/stats/base/dsmeanpn.h"
Computes the arithmetic mean of a single-precision floating-point strided array using a two-pass error correction algorithm with extended accumulation and returning an extended precision result.
constfloatx[]= {1.0f,2.0f,3.0f,4.0f,5.0f,6.0f,7.0f,8.0f };doublev=stdlib_strided_dsmeanpn(4,x,2 );// returns 4.0
The function accepts the following arguments:
- N:
[in] CBLAS_INTnumber of indexed elements. - X:
[in] float*input array. - strideX:
[in] CBLAS_INTstride length forX.
doublestdlib_strided_dsmeanpn(constCBLAS_INTN,constfloat*X,constCBLAS_INTstrideX );
Computes the arithmetic mean of a single-precision floating-point strided array using a two-pass error correction algorithm with extended accumulation and alternative indexing semantics and returning an extended precision result.
constfloatx[]= {1.0f,2.0f,3.0f,4.0f,5.0f,6.0f,7.0f,8.0f };doublev=stdlib_strided_dsmeanpn_ndarray(4,x,2,0 );// returns 4.0
The function accepts the following arguments:
- N:
[in] CBLAS_INTnumber of indexed elements. - X:
[in] float*input array. - strideX:
[in] CBLAS_INTstride length forX. - offsetX:
[in] CBLAS_INTstarting index forX.
doublestdlib_strided_dsmeanpn_ndarray(constCBLAS_INTN,constfloat*X,constCBLAS_INTstrideX,constCBLAS_INToffsetX );
#include"stdlib/stats/base/dsmeanpn.h"#include<stdio.h>intmain(void ) {// Create a strided array:constfloatx[]= {1.0f,2.0f,3.0f,4.0f,5.0f,6.0f,7.0f,8.0f };// Specify the number of elements:constintN=4;// Specify the stride length:constintstrideX=2;// Compute the arithmetic mean:doublev=stdlib_strided_dsmeanpn(N,x,strideX );// Print the result:printf("mean: %lf\n",v );}
- Neely, Peter M. 1966. "Comparison of Several Algorithms for Computation of Means, Standard Deviations and Correlation Coefficients."Communications of the ACM 9 (7). Association for Computing Machinery: 496–99. doi:10.1145/365719.365958.
- Schubert, Erich, and Michael Gertz. 2018. "Numerically Stable Parallel Computation of (Co-)Variance." InProceedings of the 30th International Conference on Scientific and Statistical Database Management. New York, NY, USA: Association for Computing Machinery. doi:10.1145/3221269.3223036.
@stdlib/stats-base/dmeanpn:calculate the arithmetic mean of a double-precision floating-point strided array using a two-pass error correction algorithm.@stdlib/stats-base/dsmean:calculate the arithmetic mean of a single-precision floating-point strided array using extended accumulation and returning an extended precision result.@stdlib/stats-base/dsnanmeanpn:calculate the arithmetic mean of a single-precision floating-point strided array, ignoring NaN values, using a two-pass error correction algorithm with extended accumulation, and returning an extended precision result.@stdlib/stats-base/meanpn:calculate the arithmetic mean of a strided array using a two-pass error correction algorithm.@stdlib/stats-base/smeanpn:calculate the arithmetic mean of a single-precision floating-point strided array using a two-pass error correction algorithm.
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Calculate the arithmetic mean of a single-precision floating-point strided array using a two-pass error correction algorithm with extended accumulation and returning an extended precision result.
