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Cosine

Raised cosine distribution constructor.

Installation

npm install @stdlib/stats-base-dists-cosine-ctor

Alternatively,

To load the package in a website via a script tag without installation and bundlers, use the ES Module available on the esm branch (see README).
If you are using Deno, visit the deno branch (see README for usage intructions).
For use in Observable, or in browser/node environments, use the Universal Module Definition (UMD) build available on the umd branch (see README).

The branches.md file summarizes the available branches and displays a diagram illustrating their relationships.

To view installation and usage instructions specific to each branch build, be sure to explicitly navigate to the respective README files on each branch, as linked to above.

Usage

var Cosine = require( '@stdlib/stats-base-dists-cosine-ctor' );

Cosine( [mu, s] )

Returns a raised cosine distribution object.

var cosine = new Cosine();

var mu = cosine.mean;
// returns 0.0

By default, mu = 0.0 and s = 1.0. To create a distribution having a different mu (location parameter) and s (scale parameter), provide the corresponding arguments.

var cosine = new Cosine( 2.0, 4.0 );

var mu = cosine.mean;
// returns 2.0

cosine

A raised cosine distribution object has the following properties and methods...

Writable Properties

cosine.mu

Location parameter of the distribution.

var cosine = new Cosine();

var mu = cosine.mu;
// returns 0.0

cosine.mu = 3.0;

mu = cosine.mu;
// returns 3.0

cosine.s

Scale parameter of the distribution. s must be a positive number.

var cosine = new Cosine( 2.0, 4.0 );

var s = cosine.s;
// returns 4.0

cosine.s = 3.0;

s = cosine.s;
// returns 3.0

Computed Properties

Cosine.prototype.kurtosis

Returns the excess kurtosis.

var cosine = new Cosine( 4.0, 12.0 );

var kurtosis = cosine.kurtosis;
// returns ~-0.594

Cosine.prototype.mean

Returns the expected value.

var cosine = new Cosine( 4.0, 12.0 );

var mu = cosine.mean;
// returns 4.0

Cosine.prototype.median

Returns the median.

var cosine = new Cosine( 4.0, 12.0 );

var median = cosine.median;
// returns 4.0

Cosine.prototype.mode

Returns the mode.

var cosine = new Cosine( 4.0, 12.0 );

var mode = cosine.mode;
// returns 4.0

Cosine.prototype.skewness

Returns the skewness.

var cosine = new Cosine( 4.0, 12.0 );

var skewness = cosine.skewness;
// returns 0.0

Cosine.prototype.stdev

Returns the standard deviation.

var cosine = new Cosine( 4.0, 12.0 );

var s = cosine.stdev;
// returns ~4.338

Cosine.prototype.variance

Returns the variance.

var cosine = new Cosine( 4.0, 12.0 );

var s2 = cosine.variance;
// returns ~18.819

Methods

Cosine.prototype.cdf( x )

Evaluates the cumulative distribution function (CDF).

var cosine = new Cosine( 2.0, 4.0 );

var y = cosine.cdf( 0.5 );
// returns ~0.165

Cosine.prototype.logcdf( x )

Evaluates the natural logarithm of the cumulative distribution function (CDF).

var cosine = new Cosine( 2.0, 4.0 );

var y = cosine.logcdf( 0.5 );
// returns ~-1.799

Cosine.prototype.logpdf( x )

Evaluates the natural logarithm of the probability density function (PDF).

var cosine = new Cosine( 2.0, 4.0 );

var y = cosine.logpdf( 0.8 );
// returns ~-1.617

Cosine.prototype.mgf( t )

Evaluates the moment-generating function (MGF).

var cosine = new Cosine( 2.0, 4.0 );

var y = cosine.mgf( 0.2 );
// returns ~1.555

Cosine.prototype.pdf( x )

Evaluates the probability density function (PDF).

var cosine = new Cosine( 2.0, 4.0 );

var y = cosine.pdf( 2.0 );
// returns 0.25

Cosine.prototype.quantile( p )

Evaluates the quantile function at probability p.

var cosine = new Cosine( 2.0, 4.0 );

var y = cosine.quantile( 0.9 );
// returns ~3.929

y = cosine.quantile( 1.9 );
// returns NaN

Examples

var Cosine = require( '@stdlib/stats-base-dists-cosine-ctor' );

var cosine = new Cosine( 2.0, 4.0 );

var mean = cosine.mean;
// returns 2.0

var median = cosine.median;
// returns 2.0

var s2 = cosine.variance;
// returns ~2.091

var y = cosine.cdf( 0.8 );
// returns ~0.221

Notice

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.

Community

License

See LICENSE.

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