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Continuous uniform distribution.
npm install @stdlib/stats-base-dists-uniformvar uniform = require( '@stdlib/stats-base-dists-uniform' );Continuous uniform distribution.
var dist = uniform;
// returns {...}The namespace contains the following distribution functions:
-
cdf( x, a, b ): uniform distribution cumulative distribution function. -
logcdf( x, a, b ): uniform distribution logarithm of cumulative distribution function. -
logpdf( x, a, b ): uniform distribution logarithm of probability density function (PDF). -
mgf( t, a, b ): uniform distribution moment-generating function (MGF). -
pdf( x, a, b ): uniform distribution probability density function (PDF). -
quantile( p, a, b ): uniform distribution quantile function.
The namespace contains the following functions for calculating distribution properties:
-
entropy( a, b ): uniform distribution differential entropy. -
kurtosis( a, b ): uniform distribution excess kurtosis. -
mean( a, b ): uniform distribution expected value. -
median( a, b ): uniform distribution median. -
skewness( a, b ): uniform distribution skewness. -
stdev( a, b ): uniform distribution standard deviation. -
variance( a, b ): uniform distribution variance.
The namespace contains a constructor function for creating a continuous uniform distribution object.
-
Uniform( [a, b] ): uniform distribution constructor.
var Uniform = require( '@stdlib/stats-base-dists-uniform' ).Uniform;
var dist = new Uniform( 2.0, 4.0 );
var y = dist.cdf( 2.5 );
// returns 0.25var uniform = require( '@stdlib/stats-base-dists-uniform' );
/*
Let's consider an example where we are modeling the arrival times of guests
at a reception event that runs from 6:00 PM to 8:00 PM, where each arrival
within this 2-hour window is equally likely. We can model this scenario using a
continuous uniform distribution with a minimum value of 0 (6:00 PM) and
a maximum value of 120 (8:00 PM).
*/
var min = 0.0; // 6:00 PM is 0 minutes after 6:00 PM.
var max = 120.0; // 8:00 PM is 120 minutes after 6:00 PM.
var mean = uniform.mean( min, max );
// returns 60.0
var variance = uniform.variance( min, max );
// returns 1200.0
var stdDev = uniform.stdev( min, max );
// returns ~34.641
var entropy = uniform.entropy( min, max );
// returns ~4.787
// Probability of arrival within 30 minutes after 6:00 PM:
var p = uniform.cdf( 30, min, max );
// returns 0.25
// Evaluate the PDF at 30 minutes after 6:00 PM:
var pdf = uniform.pdf( 30, min, max );
// returns ~0.0083This 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.
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