Covariance

!NPM versionnpm-imagenpm-url !Build Statustravis-imagetravis-url !Coverage Statuscoveralls-imagecoveralls-url !Dependenciesdependencies-imagedependencies-urlComputes the covariance between one or more numeric arrays.

## Installation

`$ npm install compute-covariance`

For use in the browser, use browserify.

## Usage

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

#### cov( arr1, arr2,...,opts )

Computes the covariance between one or more numeric arrays.```
var x = [ 1, 2, 3, 4, 5 ],
y = [ 5, 4, 3, 2, 1 ];
var mat = cov( x, y );
// returns [[2.5,-2.5],[-2.5,2.5]]
```

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

If the number of arrays is dynamic, you may want the flexibility to compute the covariance of an arbitrary

`array`

collection. To this end, `cov`

also accepts an `array`

of `arrays`

.```
var mat = cov( [x,y] );
// returns [[2.5,-2.5],[-2.5,2.5]]
```

By default, each element of the covariance matrix is an

*unbiased*covariance estimate. Hence, the covariance matrix is the

**sample covariance matrix**. For those cases where you want a biased estimate (i.e., population statistics), set the

`bias`

option to `true`

.```
var mat = cov( x, y, {'bias': true});
// returns [[2,-2],[-2,2]]
```

## Examples

```
var cov = require( 'compute-covariance' );
// 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 = cov( 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`