About stdlib...
We believe in a future in which the web is a preferred environment for numerical computation. To help realize this future, we've built stdlib. stdlib is a standard library, with an emphasis on numerical and scientific computation, written in JavaScript (and C) for execution in browsers and in Node.js.
The library is fully decomposable, being architected in such a way that you can swap out and mix and match APIs and functionality to cater to your exact preferences and use cases.
When you use stdlib, you can be absolutely certain that you are using the most thorough, rigorous, well-written, studied, documented, tested, measured, and high-quality code out there.
To join us in bringing numerical computing to the web, get started by checking us out on GitHub, and please consider financially supporting stdlib. We greatly appreciate your continued support!
Binomial
Binomial distribution constructor.
Installation
npm install @stdlib/stats-base-dists-binomial-ctor
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
License
See LICENSE.
Copyright
Copyright © 2016-2024. The Stdlib Authors.