@stdlib/stats-base-dists-triangular-ctor v0.2.2
Triangular
Triangular distribution constructor.
Installation
npm install @stdlib/stats-base-dists-triangular-ctorUsage
var Triangular = require( '@stdlib/stats-base-dists-triangular-ctor' );Triangular( [a, b, c] )
Returns a triangular distribution object.
var triangular = new Triangular();
var mu = triangular.mean;
// returns 0.5By default, a = 0.0, b = 1.0, and c = 0.5. To create a distribution having a different a (minimum support), b (maximum support), and c (mode), provide the corresponding arguments.
var triangular = new Triangular( 2.0, 4.0, 3.5 );
var mu = triangular.mean;
// returns ~3.167triangular
An triangular distribution object has the following properties and methods...
Writable Properties
triangular.a
Minimum support of the distribution. a must be a number smaller than or equal to b and c.
var triangular = new Triangular();
var a = triangular.a;
// returns 0.0
triangular.a = 0.5;
a = triangular.a;
// returns 0.5triangular.b
Maximum support of the distribution. b must be a number larger than or equal to a and c.
var triangular = new Triangular( 2.0, 4.0, 2.5 );
var b = triangular.b;
// returns 4.0
triangular.b = 3.0;
b = triangular.b;
// returns 3.0triangular.c
Mode of the distribution. c must be a number larger than or equal to a and smaller than or equal to b.
var triangular = new Triangular( 2.0, 5.0, 4.0 );
var c = triangular.c;
// returns 4.0
triangular.c = 3.0;
c = triangular.c;
// returns 3.0Computed Properties
Triangular.prototype.entropy
Returns the differential entropy.
var triangular = new Triangular( 4.0, 12.0, 10.0 );
var entropy = triangular.entropy;
// returns ~1.886Triangular.prototype.kurtosis
Returns the excess kurtosis.
var triangular = new Triangular( 4.0, 12.0, 10.0 );
var kurtosis = triangular.kurtosis;
// returns -0.6Triangular.prototype.mean
Returns the expected value.
var triangular = new Triangular( 4.0, 12.0, 10.0 );
var mu = triangular.mean;
// returns ~8.667Triangular.prototype.median
Returns the median.
var triangular = new Triangular( 4.0, 12.0, 10.0 );
var median = triangular.median;
// returns ~8.899Triangular.prototype.mode
Returns the mode.
var triangular = new Triangular( 4.0, 12.0, 10.0 );
var mode = triangular.mode;
// returns 10.0Triangular.prototype.skewness
Returns the skewness.
var triangular = new Triangular( 4.0, 12.0, 10.0 );
var skewness = triangular.skewness;
// returns ~-0.422Triangular.prototype.stdev
Returns the standard deviation.
var triangular = new Triangular( 4.0, 12.0, 10.0 );
var s = triangular.stdev;
// returns ~1.7Triangular.prototype.variance
Returns the variance.
var triangular = new Triangular( 4.0, 12.0, 10.0 );
var s2 = triangular.variance;
// returns ~2.889Methods
Triangular.prototype.cdf( x )
Evaluates the cumulative distribution function (CDF).
var triangular = new Triangular( 2.0, 4.0, 3.0 );
var y = triangular.cdf( 2.5 );
// returns 0.125Triangular.prototype.logcdf( x )
Evaluates the natural logarithm of the cumulative distribution function (CDF).
var triangular = new Triangular( 2.0, 4.0, 3.0 );
var y = triangular.logcdf( 2.5 );
// returns ~-2.079Triangular.prototype.logpdf( x )
Evaluates the natural logarithm of the probability density function (PDF).
var triangular = new Triangular( 2.0, 4.0, 3.0 );
var y = triangular.logpdf( 2.5 );
// returns ~-0.693Triangular.prototype.pdf( x )
Evaluates the probability density function (PDF).
var triangular = new Triangular( 2.0, 4.0, 3.0 );
var y = triangular.pdf( 2.5 );
// returns 0.5Triangular.prototype.quantile( p )
Evaluates the quantile function at probability p.
var triangular = new Triangular( 2.0, 4.0, 3.0 );
var y = triangular.quantile( 0.5 );
// returns 3.0
y = triangular.quantile( 1.9 );
// returns NaNExamples
var Triangular = require( '@stdlib/stats-base-dists-triangular-ctor' );
var triangular = new Triangular( 2.0, 4.0, 3.0 );
var mu = triangular.mean;
// returns 3.0
var median = triangular.median;
// returns 3.0
var s2 = triangular.variance;
// returns ~0.167
var y = triangular.cdf( 2.5 );
// returns 0.125Notice
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.
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License
See LICENSE.
Copyright
Copyright © 2016-2024. The Stdlib Authors.