# compute-nangmean

Computes the geometric mean of an array of values ignoring any values which are not numeric.

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compute-nangmean
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nangmean
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Computes the geometric mean of an array of values ignoring any values which are not numeric.

## Installation

``\$ npm install compute-nangmean``

For use in the browser, use browserify.

## Usage

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

#### nangmean( arr )

Computes the geometric mean ignoring non-numeric values.
``````var data = [ 1, 5, NaN, 2, 3, NaN, 7 ];

var mu = nangmean( data );
// returns ~2.914``````

Note: only calculate the geometric mean over an `array` containing positive numbers. The textbook formula for calculating the geometric mean involves taking the product of all `array` elements. If one element is `0`, then the product is `0`, even if all other values are `>>> 0`, yielding a nonsensical geometric mean (and measure of the central tendency). Nonsensical results also arise when an `array` contains negative values leading to a product without positive roots and a geometric mean which does not map to the measure's geometric interpretation. For more information, see Handbook of Parametric and Nonparametric Statistical Procedures: Third Edition by David J. Sheskin.
If an `array` contains numeric values less than or equal to `0`, the function returns `NaN`.

## Examples

``````var nangmean = require( 'compute-nangmean' );

var data = new Array( 1000 );
for ( var i = 0; i < data.length; i++ ) {
if ( i%5 === 0 ) {
data[ i ] = NaN;
} else {
data[ i ] = Math.random() * 100;
}
}

console.log( nangmean( data ) );``````

To run the example code from the top-level application directory,
``\$ node ./examples/index.js``

## Notes

The geometric mean of an array containing non-numeric values is equal to the geometric mean of an equivalent array which contains only the numeric values. Hence,
``````var d1 = [ 1, NaN, 2, 3, NaN ],
d2 = [ 1, 2, 3 ];

console.log( nangmean( d1 ) === nangmean( d2 ) );
// returns true``````

## 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``