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Triangular
Triangular distribution constructor.
Installation
npm install @stdlib/stats-base-dists-triangular-ctor
Usage
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 0.5
By 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 ~3.167
triangular
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 0.5
triangular.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 3.0
triangular.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 3.0
Computed Properties
Triangular.prototype.entropy
Returns the differential entropy.
var triangular = new Triangular( 4.0, 12.0, 10.0 );
var entropy = triangular.entropy;
// returns ~1.886
Triangular.prototype.kurtosis
Returns the excess kurtosis.
var triangular = new Triangular( 4.0, 12.0, 10.0 );
var kurtosis = triangular.kurtosis;
// returns -0.6
Triangular.prototype.mean
Returns the expected value.
var triangular = new Triangular( 4.0, 12.0, 10.0 );
var mu = triangular.mean;
// returns ~8.667
Triangular.prototype.median
Returns the median.
var triangular = new Triangular( 4.0, 12.0, 10.0 );
var median = triangular.median;
// returns ~8.899
Triangular.prototype.mode
Returns the mode.
var triangular = new Triangular( 4.0, 12.0, 10.0 );
var mode = triangular.mode;
// returns 10.0
Triangular.prototype.skewness
Returns the skewness.
var triangular = new Triangular( 4.0, 12.0, 10.0 );
var skewness = triangular.skewness;
// returns ~-0.422
Triangular.prototype.stdev
Returns the standard deviation.
var triangular = new Triangular( 4.0, 12.0, 10.0 );
var s = triangular.stdev;
// returns ~1.7
Triangular.prototype.variance
Returns the variance.
var triangular = new Triangular( 4.0, 12.0, 10.0 );
var s2 = triangular.variance;
// returns ~2.889
Methods
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 0.125
Triangular.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 ~-2.079
Triangular.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 ~-0.693
Triangular.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 0.5
Triangular.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 NaN
Examples
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 0.125
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.