@stdlib/stats-base-ndarray-stdev
v0.1.1
Published
Compute the standard deviation of a one-dimensional ndarray.
Readme
stdev
Calculate the standard deviation of a one-dimensional ndarray.
The population standard deviation of a finite size population of size N is given by
where the population mean is given by
Often in the analysis of data, the true population standard deviation is not known a priori and must be estimated from a sample drawn from the population distribution. If one attempts to use the formula for the population standard deviation, the result is biased and yields an uncorrected sample standard deviation. To compute a corrected sample standard deviation for a sample of size n,
where the sample mean is given by
The use of the term n-1 is commonly referred to as Bessel's correction. Note, however, that applying Bessel's correction can increase the mean squared error between the sample standard deviation and population standard deviation. Depending on the characteristics of the population distribution, other correction factors (e.g., n-1.5, n+1, etc) can yield better estimators.
Installation
npm install @stdlib/stats-base-ndarray-stdevUsage
var stdev = require( '@stdlib/stats-base-ndarray-stdev' );stdev( arrays )
Computes the standard deviation of a one-dimensional ndarray.
var ndarray = require( '@stdlib/ndarray-base-ctor' );
var scalar2ndarray = require( '@stdlib/ndarray-from-scalar' );
var opts = {
'dtype': 'generic'
};
var xbuf = [ 1.0, -2.0, 2.0 ];
var x = new ndarray( opts.dtype, xbuf, [ 3 ], [ 1 ], 0, 'row-major' );
var correction = scalar2ndarray( 1.0, opts );
var v = stdev( [ x, correction ] );
// returns ~2.0817The function has the following parameters:
- arrays: array-like object containing two elements: a one-dimensional input ndarray and a zero-dimensional ndarray specifying the degrees of freedom adjustment. Providing a non-zero degrees of freedom adjustment has the effect of adjusting the divisor during the calculation of the standard deviation according to
N-cwhereNis the number of elements in the input ndarray andccorresponds to the provided degrees of freedom adjustment. When computing the standard deviation of a population, setting this parameter to0is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the corrected sample standard deviation, setting this parameter to1is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction).
Notes
- If provided an empty one-dimensional ndarray, the function returns
NaN. - If
N - cis less than or equal to0(whereNcorresponds to the number of elements in the input ndarray andccorresponds to the provided degrees of freedom adjustment), the function returnsNaN.
Examples
var discreteUniform = require( '@stdlib/random-array-discrete-uniform' );
var ndarray = require( '@stdlib/ndarray-base-ctor' );
var scalar2ndarray = require( '@stdlib/ndarray-from-scalar' );
var ndarray2array = require( '@stdlib/ndarray-to-array' );
var stdev = require( '@stdlib/stats-base-ndarray-stdev' );
var opts = {
'dtype': 'float64'
};
var xbuf = discreteUniform( 10, -50, 50, opts );
var x = new ndarray( opts.dtype, xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' );
console.log( ndarray2array( x ) );
var correction = scalar2ndarray( 1.0, opts );
var v = stdev( [ x, correction ] );
console.log( v );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 © 2016-2026. The Stdlib Authors.
