Compute a sample Pearson product-moment correlation distance.
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> Compute a [sample Pearson product-moment correlation distance][pearson-correlation] incrementally.
The [sample Pearson product-moment correlation distance][pearson-correlation] is defined as
where r is the [sample Pearson product-moment correlation coefficient][pearson-correlation], cov(x,y) is the sample covariance, and σ corresponds to the sample standard deviation. As r resides on the interval [-1,1], d resides on the interval [0,2].
``bash`
npm install @stdlib/stats-incr-pcorrdist
`javascript`
var incrpcorrdist = require( '@stdlib/stats-incr-pcorrdist' );
#### incrpcorrdist( \[mx, my] )
Returns an accumulator function which incrementally computes a [sample Pearson product-moment correlation distance][pearson-correlation].
`javascript`
var accumulator = incrpcorrdist();
If the means are already known, provide mx and my arguments.
`javascript`
var accumulator = incrpcorrdist( 3.0, -5.5 );
#### accumulator( \[x, y] )
If provided input value x and y, the accumulator function returns an updated [sample correlation coefficient][pearson-correlation]. If not provided input values x and y, the accumulator function returns the current [sample correlation coefficient][pearson-correlation].
`javascript
var accumulator = incrpcorrdist();
var d = accumulator( 2.0, 1.0 );
// returns 1.0
d = accumulator( 1.0, -5.0 );
// returns 0.0
d = accumulator( 3.0, 3.14 );
// returns ~0.035
d = accumulator();
// returns ~0.035
`
- 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.
`javascript
var randu = require( '@stdlib/random-base-randu' );
var incrpcorrdist = require( '@stdlib/stats-incr-pcorrdist' );
var accumulator;
var x;
var y;
var i;
// Initialize an accumulator:
accumulator = incrpcorrdist();
// For each simulated datum, update the sample correlation distance...
for ( i = 0; i < 100; i++ ) {
x = randu() * 100.0;
y = randu() * 100.0;
accumulator( x, y );
}
console.log( accumulator() );
`
*
- [@stdlib/stats-incr/covariance][@stdlib/stats/incr/covariance]: compute an unbiased sample covariance incrementally.
- [@stdlib/stats-incr/pcorr][@stdlib/stats/incr/pcorr]: compute a sample Pearson product-moment correlation coefficient.
- [@stdlib/stats-incr/summary][@stdlib/stats/incr/summary]: compute a statistical summary incrementally.
*
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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