stdlib-js / stats-base-dists-binomial-ctor

Binomial distribution constructor.

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Binomial

Binomial distribution constructor.

Installation

npm install @stdlib/stats-base-dists-binomial-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 Binomial = require( '@stdlib/stats-base-dists-binomial-ctor' );

Binomial( [n, p] )

Returns a binomial distribution object.

var binomial = new Binomial();

var mu = binomial.mean;
// returns 0.5

By default, n = 1 and p = 0.5, which corresponds to a Bernoulli distribution. To create a distribution having a different n (number of trials) and p (success probability), provide the corresponding arguments.

var binomial = new Binomial( 4, 0.2 );

var mu = binomial.mean;
// returns 0.8

---

binomial

A binomial distribution object has the following properties and methods...

Writable Properties

binomial.n

Number of trials of the distribution. n must be a positive integer.

var binomial = new Binomial();

var n = binomial.n;
// returns 1.0

binomial.n = 4;

n = binomial.n;
// returns 4.0

binomial.p

Success probability of the distribution. p must be a number between 0 and 1.

var binomial = new Binomial( 4, 0.2 );

var p = binomial.p;
// returns 0.2

binomial.p = 0.7;

p = binomial.p;
// returns 0.7

---

Computed Properties

Binomial.prototype.kurtosis

Returns the excess kurtosis.

var binomial = new Binomial( 12, 0.4 );

var kurtosis = binomial.kurtosis;
// returns ~-0.153

Binomial.prototype.mean

Returns the expected value.

var binomial = new Binomial( 12, 0.4 );

var mu = binomial.mean;
// returns ~4.8

Binomial.prototype.median

Returns the median.

var binomial = new Binomial( 12, 0.4 );

var median = binomial.median;
// returns 5.0

Binomial.prototype.mode

Returns the mode.

var binomial = new Binomial( 12, 0.4 );

var mode = binomial.mode;
// returns 5.0

Binomial.prototype.skewness

Returns the skewness.

var binomial = new Binomial( 12, 0.4 );

var skewness = binomial.skewness;
// returns ~0.118

Binomial.prototype.stdev

Returns the standard deviation.

var binomial = new Binomial( 12, 0.4 );

var s = binomial.stdev;
// returns ~1.697

Binomial.prototype.variance

Returns the variance.

var binomial = new Binomial( 12, 0.4 );

var s2 = binomial.variance;
// returns ~2.88

---

Methods

Binomial.prototype.cdf( x )

Evaluates the cumulative distribution function (CDF).

var binomial = new Binomial( 4, 0.2 );

var y = binomial.cdf( 0.5 );
// returns ~0.41

Binomial.prototype.logpmf( x )

Evaluates the natural logarithm of the probability mass function (PMF).

var binomial = new Binomial( 4, 0.2 );

var y = binomial.logpmf( 2.0 );
// returns ~-1.873

Binomial.prototype.mgf( t )

Evaluates the moment-generating function (MGF).

var binomial = new Binomial( 4, 0.2 );

var y = binomial.mgf( 0.5 );
// returns ~1.629

Binomial.prototype.pmf( x )

Evaluates the probability mass function (PMF).

var binomial = new Binomial( 4, 0.2 );

var y = binomial.pmf( 2.0 );
// returns ~0.154

Binomial.prototype.quantile( p )

Evaluates the quantile function at probability p.

var binomial = new Binomial( 4, 0.2 );

var y = binomial.quantile( 0.5 );
// returns 1.0

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

---

Examples

var Binomial = require( '@stdlib/stats-base-dists-binomial-ctor' );

var binomial = new Binomial( 10, 0.4 );

var mu = binomial.mean;
// returns 4.0

var mode = binomial.mode;
// returns 4.0

var s2 = binomial.variance;
// returns 2.4

var y = binomial.cdf( 0.8 );
// returns ~0.006

---

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

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License

See LICENSE.

Copyright

Copyright © 2016-2024. The Stdlib Authors.