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Compute a moving sample Pearson productmoment correlation coefficient incrementally.
The Pearson productmoment correlation coefficient between random variables X
and Y
is defined as
where the numerator is the covariance and the denominator is the product of the respective standard deviations.
For a sample of size W
, the sample Pearson productmoment correlation coefficient is defined as
npm install @stdlib/statsincrmpcorr
var incrmpcorr = require( '@stdlib/statsincrmpcorr' );
Returns an accumulator function
which incrementally computes a moving sample Pearson productmoment correlation coefficient. The window
parameter defines the number of values over which to compute the moving sample Pearson productmoment correlation coefficient.
var accumulator = incrmpcorr( 3 );
If means are already known, provide mx
and my
arguments.
var accumulator = incrmpcorr( 3, 5.0, 3.14 );
If provided input values x
and y
, the accumulator function returns an updated sample Pearson productmoment correlation coefficient. If not provided input values x
and y
, the accumulator function returns the current sample Pearson productmoment correlation coefficient.
var accumulator = incrmpcorr( 3 );
var r = accumulator();
// returns null
// Fill the window...
r = accumulator( 2.0, 1.0 ); // [(2.0, 1.0)]
// returns 0.0
r = accumulator( 5.0, 3.14 ); // [(2.0, 1.0), (5.0, 3.14)]
// returns ~1.0
r = accumulator( 3.0, 1.0 ); // [(2.0, 1.0), (5.0, 3.14), (3.0, 1.0)]
// returns ~0.925
// Window begins sliding...
r = accumulator( 5.0, 9.5 ); // [(5.0, 3.14), (3.0, 1.0), (5.0, 9.5)]
// returns ~0.863
r = accumulator( 5.0, 1.5 ); // [(3.0, 1.0), (5.0, 9.5), (5.0, 1.5)]
// returns ~0.803
r = accumulator();
// returns ~0.803
 Input values are not type checked. If provided
NaN
or a value which, when used in computations, results inNaN
, the accumulated value isNaN
for at leastW1
future invocations. If nonnumeric inputs are possible, you are advised to type check and handle accordingly before passing the value to the accumulator function.  As
W
(x,y) pairs are needed to fill the window buffer, the firstW1
returned values are calculated from smaller sample sizes. Until the window is full, each returned value is calculated from all provided values.
var randu = require( '@stdlib/randombaserandu' );
var incrmpcorr = require( '@stdlib/statsincrmpcorr' );
var accumulator;
var x;
var y;
var i;
// Initialize an accumulator:
accumulator = incrmpcorr( 5 );
// For each simulated datum, update the moving sample correlation coefficient...
for ( i = 0; i < 100; i++ ) {
x = randu() * 100.0;
y = randu() * 100.0;
accumulator( x, y );
}
console.log( accumulator() );

@stdlib/statsincr/mcovariance
: compute a moving unbiased sample covariance incrementally. 
@stdlib/statsincr/mpcorrdist
: compute a moving sample Pearson productmoment correlation distance incrementally. 
@stdlib/statsincr/pcorr
: compute a sample Pearson productmoment correlation coefficient.
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.
See LICENSE.
Copyright © 20162024. The Stdlib Authors.