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Raised cosine distribution.
To use in Observable,
cosine = require( 'https://cdn.jsdelivr.net/gh/stdlib-js/stats-base-dists-cosine@umd/browser.js' )To vendor stdlib functionality and avoid installing dependency trees for Node.js, you can use the UMD server build:
var cosine = require( 'path/to/vendor/umd/stats-base-dists-cosine/index.js' )To include the bundle in a webpage,
<script type="text/javascript" src="https://cdn.jsdelivr.net/gh/stdlib-js/stats-base-dists-cosine@umd/browser.js"></script>If no recognized module system is present, access bundle contents via the global scope:
<script type="text/javascript">
(function () {
window.cosine;
})();
</script>Raised cosine distribution.
var dist = cosine;
// returns {...}The namespace contains the following distribution functions:
cdf( x, mu, s ): raised cosine distribution cumulative distribution function.logcdf( x, mu, s ): evaluate the natural logarithm of the cumulative distribution function (CDF) for a raised cosine distribution.logpdf( x, mu, s ): raised cosine distribution logarithm of probability density function (PDF).mgf( t, mu, s ): raised cosine distribution moment-generating function.pdf( x, mu, s ): raised cosine distribution probability density function (PDF).quantile( p, mu, s ): raised cosine distribution quantile function.
The namespace contains the following functions for calculating distribution properties:
kurtosis( mu, s ): raised cosine distribution excess kurtosis.mean( mu, s ): raised cosine distribution expected value.median( mu, s ): raised cosine distribution median.mode( mu, s ): raised cosine distribution mode.skewness( mu, s ): raised cosine distribution skewness.stdev( mu, s ): raised cosine distribution standard deviation.variance( mu, s ): raised cosine distribution variance.
The namespace contains a constructor function for creating a raised cosine distribution object.
Cosine( [mu, s] ): raised cosine distribution constructor.
var Cosine = require( '@stdlib/stats-base-dists-cosine' ).Cosine;
var dist = new Cosine( 2.0, 4.0 );
var y = dist.cdf( 0.5 );
// returns ~0.165<!DOCTYPE html>
<html lang="en">
<body>
<script type="text/javascript" src="https://cdn.jsdelivr.net/gh/stdlib-js/stats-base-dists-cosine@umd/browser.js"></script>
<script type="text/javascript">
(function () {
// Create a raised cosine distribution:
var mu = 2.0;
var s = 1.5;
var dist = new cosine.Cosine( mu, s );
// Calculate various distribution properties:
console.log( 'Mean: %d', dist.mean );
// => 'Mean: 2'
console.log( 'Median: %d', dist.median );
// => 'Median: 2'
console.log( 'Mode: %d', dist.mode );
// => 'Mode: 2'
console.log( 'Standard Deviation: %d', dist.stdev );
// => 'Standard Deviation: 0.5422680827869919'
console.log( 'Variance: %d', dist.variance );
// => 'Variance: 0.29405467360947996'
// Evaluate the probability density function (PDF):
var x = 1.5;
console.log( 'PDF( %d ): %d', x, dist.pdf( x ) );
// => 'PDF( 1.5 ): 0.5'
// Evaluate the cumulative distribution function (CDF):
console.log( 'CDF( %d ): %d', x, dist.cdf( x ) );
// => 'CDF( 1.5 ): 0.19550110947788535'
// Calculate distribution moments:
console.log( 'Skewness: %d', cosine.skewness( mu, s ) );
// => 'Skewness: 0'
console.log( 'Excess Kurtosis: %d', cosine.kurtosis( mu, s ) );
// => 'Excess Kurtosis: -0.5937628755982807'
})();
</script>
</body>
</html>This package is part of stdlib, a standard library for JavaScript and Node.js, with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more.
For more information on the project, filing bug reports and feature requests, and guidance on how to develop stdlib, see the main project repository.
See LICENSE.
Copyright © 2016-2024. The Stdlib Authors.