Correlation Matrix

!NPM versionnpm-imagenpm-url !Build Statustravis-imagetravis-url !Coverage Statuscoveralls-imagecoveralls-url !Dependenciesdependencies-imagedependencies-urlComputes Pearson product-moment correlation coefficients between one or more numeric arrays.

## Installation

`$ npm install compute-pcorr`

For use in the browser, use browserify.

## Usage

To use the module,`var pcorr = require( 'compute-pcorr' );`

#### pcorr( arr1, arr2,... )

Computes Pearson product-moment correlation coefficients between one or more numeric arrays.```
var x = [ 1, 2, 3, 4, 5 ],
y = [ 5, 4, 3, 2, 1 ];
var mat = pcorr( x, y );
// returns [[1,-1],[-1,1]]
```

Note: for univariate input, the returned correlation matrix contains a single element equal to unity.

If the number of arrays is dynamic, you may want the flexibility to compute linear correlation coefficients for an arbitrary

`array`

collection. To this end, the function also accepts an `array`

of `arrays`

.```
var mat = pcorr( [x,y] );
// returns [[1,-1],[-1,1]]
```

## Notes

**Beware**of floating point errors. Computing a linear correlation coefficient requires computing square roots and involves division. Both operations can introduce small errors during calculation.

Efforts have been made to ensure no value exceeds

`+-1`

. Note, however, that perfectly correlated `arrays`

are **not**guaranteed to yield precise correlation coefficients of

`+-1`

. ## Examples

```
var pcorr = require( 'compute-pcorr' );
// Simulate some data...
var N = 100,
x = new Array( N ),
y = new Array( N ),
z = new Array( N );
for ( var i = 0; i < N; i++ ) {
x[ i ] = Math.round( Math.random()*100 );
y[ i ] = Math.round( Math.random()*100 );
z[ i ] = 100 - x[ i ];
}
var mat = pcorr( x, y, z );
console.log( mat );
```

To run the example code from the top-level application directory,

`$ node ./examples/index.js`

## Tests

### Unit

Unit tests use the Mocha test framework with Chai assertions. To run the tests, execute the following command in the top-level application directory:`$ make test`

All new feature development should have corresponding unit tests to validate correct functionality.

### Test Coverage

This repository uses Istanbul as its code coverage tool. To generate a test coverage report, execute the following command in the top-level application directory:`$ make test-cov`

Istanbul creates a

`./reports/coverage`

directory. To access an HTML version of the report,`$ make view-cov`