# incrpcorr

Compute a sample Pearson product-moment correlation coefficient incrementally.

The Pearson product-moment 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 `n`

, the sample Pearson product-moment correlation coefficient is defined as

## Usage

```
var incrpcorr = require( '@stdlib/stats/incr/pcorr' );
```

#### incrpcorr( [mx, my] )

Returns an accumulator `function`

which incrementally computes a sample Pearson product-moment correlation coefficient.

```
var accumulator = incrpcorr();
```

If the means are already known, provide `mx`

and `my`

arguments.

```
var accumulator = incrpcorr( 3.0, -5.5 );
```

#### accumulator( [x, y] )

If provided input value `x`

and `y`

, the accumulator function returns an updated sample correlation coefficient. If not provided input values `x`

and `y`

, the accumulator function returns the current sample correlation coefficient.

```
var accumulator = incrpcorr();
var v = accumulator( 2.0, 1.0 );
// returns 0.0
v = accumulator( 1.0, -5.0 );
// returns 1.0
v = accumulator( 3.0, 3.14 );
// returns ~0.965
v = accumulator();
// returns ~0.965
```

## Notes

- 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.

## Examples

```
var randu = require( '@stdlib/random/base/randu' );
var incrpcorr = require( '@stdlib/stats/incr/pcorr' );
var accumulator;
var x;
var y;
var i;
// Initialize an accumulator:
accumulator = incrpcorr();
// For each simulated datum, update the sample correlation coefficient...
for ( i = 0; i < 100; i++ ) {
x = randu() * 100.0;
y = randu() * 100.0;
accumulator( x, y );
}
console.log( accumulator() );
```