Compute a squared sample Pearson product-moment correlation coefficient.
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> Compute a squared sample [Pearson product-moment correlation coefficient][pearson-correlation] incrementally.
The [Pearson product-moment correlation coefficient][pearson-correlation] between random variables X and Y is defined as
where the numerator is the [covariance][covariance] and the denominator is the product of the respective standard deviations.
For a sample of size n, the sample [Pearson product-moment correlation coefficient][pearson-correlation] is defined as
The squared sample [Pearson product-moment correlation coefficient][pearson-correlation] is thus defined as the square of the sample [Pearson product-moment correlation coefficient][pearson-correlation].
``bash`
npm install @stdlib/stats-incr-pcorr2
`javascript`
var incrpcorr2 = require( '@stdlib/stats-incr-pcorr2' );
#### incrpcorr2( \[mx, my] )
Returns an accumulator function which incrementally computes a squared sample [Pearson product-moment correlation coefficient][pearson-correlation].
`javascript`
var accumulator = incrpcorr2();
If the means are already known, provide mx and my arguments.
`javascript`
var accumulator = incrpcorr2( 3.0, -5.5 );
#### accumulator( \[x, y] )
If provided input value x and y, the accumulator function returns an updated accumulated value. If not provided input values x and y, the accumulator function returns the current accumulated value.
`javascript
var accumulator = incrpcorr2();
var r2 = accumulator( 2.0, 1.0 );
// returns 0.0
r2 = accumulator( 1.0, -5.0 );
// returns 1.0
r2 = accumulator( 3.0, 3.14 );
// returns ~0.93
r2 = accumulator();
// returns ~0.93
`
- Input values are not type checked. If provided NaN or a value which, when used in computations, results in NaN, the accumulated value is NaN for all future invocations. If non-numeric inputs are possible, you are advised to type check and handle accordingly before passing the value to the accumulator function.
- In comparison to the sample [Pearson product-moment correlation coefficient][pearson-correlation], the squared sample [Pearson product-moment correlation coefficient][pearson-correlation] is useful for emphasizing strong correlations.
`javascript
var randu = require( '@stdlib/random-base-randu' );
var incrpcorr2 = require( '@stdlib/stats-incr-pcorr2' );
var accumulator;
var x;
var y;
var i;
// Initialize an accumulator:
accumulator = incrpcorr2();
// For each simulated datum, update the squared sample correlation coefficient...
for ( i = 0; i < 100; i++ ) {
x = randu() * 100.0;
y = randu() * 100.0;
accumulator( x, y );
}
console.log( accumulator() );
`
*
- [@stdlib/stats-incr/apcorr][@stdlib/stats/incr/apcorr]: compute a sample absolute Pearson product-moment correlation coefficient.
- [@stdlib/stats-incr/mpcorr2][@stdlib/stats/incr/mpcorr2]: compute a moving squared sample Pearson product-moment correlation coefficient incrementally.
- [@stdlib/stats-incr/pcorr][@stdlib/stats/incr/pcorr]: compute a sample Pearson product-moment correlation coefficient.
*
This package is part of [stdlib][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][stdlib], see the main project [repository][stdlib].
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---
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[pearson-correlation]: https://en.wikipedia.org/wiki/Pearson_correlation_coefficient
[covariance]: https://en.wikipedia.org/wiki/Covariance
[@stdlib/stats/incr/apcorr]: https://www.npmjs.com/package/@stdlib/stats-incr-apcorr
[@stdlib/stats/incr/mpcorr2]: https://www.npmjs.com/package/@stdlib/stats-incr-mpcorr2
[@stdlib/stats/incr/pcorr]: https://www.npmjs.com/package/@stdlib/stats-incr-pcorr