npm package discovery and stats viewer.

Discover Tips

  • General search

    [free text search, go nuts!]

  • Package details

    pkg:[package-name]

  • User packages

    @[username]

Sponsor

Optimize Toolset

I’ve always been into building performant and accessible sites, but lately I’ve been taking it extremely seriously. So much so that I’ve been building a tool to help me optimize and monitor the sites that I build to make sure that I’m making an attempt to offer the best experience to those who visit them. If you’re into performant, accessible and SEO friendly sites, you might like it too! You can check it out at Optimize Toolset.

About

Hi, 👋, I’m Ryan Hefner  and I built this site for me, and you! The goal of this site was to provide an easy way for me to check the stats on my npm packages, both for prioritizing issues and updates, and to give me a little kick in the pants to keep up on stuff.

As I was building it, I realized that I was actually using the tool to build the tool, and figured I might as well put this out there and hopefully others will find it to be a fast and useful way to search and browse npm packages as I have.

If you’re interested in other things I’m working on, follow me on Twitter or check out the open source projects I’ve been publishing on GitHub.

I am also working on a Twitter bot for this site to tweet the most popular, newest, random packages from npm. Please follow that account now and it will start sending out packages soon–ish.

Open Software & Tools

This site wouldn’t be possible without the immense generosity and tireless efforts from the people who make contributions to the world and share their work via open source initiatives. Thank you 🙏

© 2024 – Pkg Stats / Ryan Hefner

distributions-rayleigh-ekurtosis

v0.0.0

Published

Rayleigh distribution excess kurtosis.

Downloads

3

Readme

Excess Kurtosis

NPM version Build Status Coverage Status Dependencies

Rayleigh distribution excess kurtosis.

The excess kurtosis for a Rayleigh random variable is

where sigma > 0 is the scale parameter.

Installation

$ npm install distributions-rayleigh-ekurtosis

For use in the browser, use browserify.

Usage

var ekurtosis = require( 'distributions-rayleigh-ekurtosis' );

ekurtosis( sigma[, opts] )

Computes the excess kurtosis for a Rayleigh distribution with parameter sigma. sigma may be either a number, an array, a typed array, or a matrix.

var matrix = require( 'dstructs-matrix' ),
	data,
	mat,
	out,
	i;

out = ekurtosis( 0.5 );
// returns ~0.245

sigma = [ 0.5, 1, 2, 4 ];
out = ekurtosis( sigma );

// returns [ ~0.245, ~0.245, ~0.245, ~0.245 ]

sigma = new Float32Array( sigma );
out = ekurtosis( sigma );
// returns Float64Array( [~0.245,~0.245,~0.245,~0.245] )

sigma =  matrix( [ 0.5, 1, 2, 4 ], [2,2] );
/*
	[ 0.5 1
	  2 4 ]
*/

out = ekurtosis( sigma );
/*
	[ ~0.245 ~0.245
	  ~0.245 ~0.245 ]
*/

The function accepts the following options:

  • accessor: accessor function for accessing array values.
  • dtype: output typed array or matrix data type. Default: float64.
  • copy: boolean indicating if the function should return a new data structure. Default: true.
  • path: deepget/deepset key path.
  • sep: deepget/deepset key path separator. Default: '.'.

For non-numeric arrays, provide an accessor function for accessing array values.

var sigma = [
	[0,0.5],
	[1,1],
	[2,2],
	[3,4]
];

function getValue( d, i ) {
	return d[ 1 ];
}

var out = ekurtosis( sigma, {
	'accessor': getValue
});
// returns [ ~0.245, ~0.245, ~0.245, ~0.245 ]

To deepset an object array, provide a key path and, optionally, a key path separator.

var sigma = [
	{'x':[9,0.5]},
	{'x':[9,1]},
	{'x':[9,2]},
	{'x':[9,4]}
];

var out = ekurtosis( sigma, {
	'path': 'x|1',
	'sep': '|'
});
/*
	[
		{'x':[9,~0.245]},
		{'x':[9,~0.245]},
		{'x':[9,~0.245]},
		{'x':[9,~0.245]},
	]
*/

var bool = ( data === out );
// returns true

By default, when provided a typed array or matrix, the output data structure is float64 in order to preserve precision. To specify a different data type, set the dtype option (see matrix for a list of acceptable data types).

var sigma, out;

sigma = new Float64Array( [ 0.5,1,2,4 ] );

out = ekurtosis( sigma, {
	'dtype': 'int32'
});
// returns Int32Array( [ 0,0,0,0 ] )

// Works for plain arrays, as well...
out = ekurtosis( [0.5,1,2,4], {
	'dtype': 'int32'
});
// returns Int32Array( [ 0,0,0,0 ] )

By default, the function returns a new data structure. To mutate the input data structure (e.g., when input values can be discarded or when optimizing memory usage), set the copy option to false.

var sigma,
	bool,
	mat,
	out,
	i;

sigma = [ 0.5, 1, 2, 4 ];

out = ekurtosis( sigma, {
	'copy': false
});
// returns [ ~0.245, ~0.245, ~0.245, ~0.245 ]

bool = ( data === out );
// returns true

mat = matrix( [ 0.5, 1, 2, 4 ], [2,2] );
/*
	[ 0.5 1
	  2 4 ]
*/

out = ekurtosis( mat, {
	'copy': false
});
/*
	[ ~0.245 ~0.245
	  ~0.245 ~0.245 ]
*/

bool = ( mat === out );
// returns true

Notes

  • If an element is not a positive number, the excess kurtosis is NaN.

    var sigma, out;
    
    out = ekurtosis( -1 );
    // returns NaN
    
    out = ekurtosis( 0 );
    // returns NaN
    
    out = ekurtosis( null );
    // returns NaN
    
    out = ekurtosis( true );
    // returns NaN
    
    out = ekurtosis( {'a':'b'} );
    // returns NaN
    
    out = ekurtosis( [ true, null, [] ] );
    // returns [ NaN, NaN, NaN ]
    
    function getValue( d, i ) {
    	return d.x;
    }
    sigma = [
    	{'x':true},
    	{'x':[]},
    	{'x':{}},
    	{'x':null}
    ];
    
    out = ekurtosis( sigma, {
    	'accessor': getValue
    });
    // returns [ NaN, NaN, NaN, NaN ]
    
    out = ekurtosis( sigma, {
    	'path': 'x'
    });
    /*
    	[
    		{'x':NaN},
    		{'x':NaN},
    		{'x':NaN,
    		{'x':NaN}
    	]
    */
  • Be careful when providing a data structure which contains non-numeric elements and specifying an integer output data type, as NaN values are cast to 0.

    var out = ekurtosis( [ true, null, [] ], {
    	'dtype': 'int8'
    });
    // returns Int8Array( [0,0,0] );

Examples

var matrix = require( 'dstructs-matrix' ),
	ekurtosis = require( 'distributions-rayleigh-ekurtosis' );

var sigma,
	mat,
	out,
	tmp,
	i;

// Plain arrays...
sigma = new Array( 10 );
for ( i = 0; i < sigma.length; i++ ) {
	sigma[ i ] = i + 1;
}
out = ekurtosis( sigma );

// Object arrays (accessors)...
function getValue( d ) {
	return d.x;
}
for ( i = 0; i < sigma.length; i++ ) {
	sigma[ i ] = {
		'x': sigma[ i ]
	};
}
out = ekurtosis( sigma, {
	'accessor': getValue
});

// Deep set arrays...
for ( i = 0; i < sigma.length; i++ ) {
	sigma[ i ] = {
		'x': [ i, sigma[ i ].x ]
	};
}
out = ekurtosis( sigma, {
	'path': 'x/1',
	'sep': '/'
});

// Typed arrays...
sigma = new Float64Array( 10 );
for ( i = 0; i < sigma.length; i++ ) {
	sigma[ i ] = i + 1;
}
out = ekurtosis( sigma );

// Matrices...
mat = matrix( sigma, [5,2], 'float64' );
out = ekurtosis( mat );

// Matrices (custom output data type)...
out = ekurtosis( mat, {
	'dtype': 'uint8'
});

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

License

MIT license.

Copyright

Copyright © 2015. The Compute.io Authors.