Kumaraswamy
Kumaraswamy's double bounded distribution constructor.
Usage
var Kumaraswamy = require( '@stdlib/stats/base/dists/kumaraswamy/ctor' );
Kumaraswamy( [a, b] )
Returns a Kumaraswamy's double bounded distribution object.
var kumaraswamy = new Kumaraswamy();
var mu = kumaraswamy.mean;
// returns 0.5
By default, a = 1.0
and b = 1.0
. To create a distribution having a different a
(first shape parameter) and b
(second shape parameter), provide the corresponding arguments.
var kumaraswamy = new Kumaraswamy( 2.0, 4.0 );
var mu = kumaraswamy.mean;
// returns ~0.406
kumaraswamy
A Kumaraswamy's double bounded distribution object has the following properties and methods...
Writable Properties
kumaraswamy.a
First shape parameter of the distribution. a
must be a positive number.
var kumaraswamy = new Kumaraswamy();
var a = kumaraswamy.a;
// returns 1.0
kumaraswamy.a = 3.0;
a = kumaraswamy.a;
// returns 3.0
kumaraswamy.b
Second shape parameter of the distribution. b
must be a positive number.
var kumaraswamy = new Kumaraswamy( 2.0, 4.0 );
var b = kumaraswamy.b;
// returns 4.0
kumaraswamy.b = 3.0;
b = kumaraswamy.b;
// returns 3.0
Computed Properties
Kumaraswamy.prototype.kurtosis
Returns the excess kurtosis.
var kumaraswamy = new Kumaraswamy( 4.0, 12.0 );
var kurtosis = kumaraswamy.kurtosis;
// returns ~2.704
Kumaraswamy.prototype.mean
Returns the expected value.
var kumaraswamy = new Kumaraswamy( 4.0, 12.0 );
var mu = kumaraswamy.mean;
// returns ~0.481
Kumaraswamy.prototype.mode
Returns the mode.
var kumaraswamy = new Kumaraswamy( 4.0, 12.0 );
var mode = kumaraswamy.mode;
// returns ~0.503
Kumaraswamy.prototype.skewness
Returns the skewness.
var kumaraswamy = new Kumaraswamy( 4.0, 12.0 );
var skewness = kumaraswamy.skewness;
// returns ~-0.201
Kumaraswamy.prototype.stdev
Returns the standard deviation.
var kumaraswamy = new Kumaraswamy( 4.0, 12.0 );
var s = kumaraswamy.stdev;
// returns ~0.13
Kumaraswamy.prototype.variance
Returns the variance.
var kumaraswamy = new Kumaraswamy( 4.0, 12.0 );
var s2 = kumaraswamy.variance;
// returns ~0.017
Methods
Kumaraswamy.prototype.cdf( x )
Evaluates the cumulative distribution function (CDF).
var kumaraswamy = new Kumaraswamy( 2.0, 4.0 );
var y = kumaraswamy.cdf( 0.5 );
// returns ~0.684
Kumaraswamy.prototype.logcdf( x )
Evaluates the natural logarithm of the cumulative distribution function (CDF).
var kumaraswamy = new Kumaraswamy( 2.0, 4.0 );
var y = kumaraswamy.logcdf( 0.5 );
// returns ~-0.38
Kumaraswamy.prototype.logpdf( x )
Evaluates the natural logarithm of the probability density function (PDF).
var kumaraswamy = new Kumaraswamy( 2.0, 4.0 );
var y = kumaraswamy.logpdf( 0.8 );
// returns ~-1.209
Kumaraswamy.prototype.pdf( x )
Evaluates the probability density function (PDF).
var kumaraswamy = new Kumaraswamy( 2.0, 4.0 );
var y = kumaraswamy.pdf( 0.8 );
// returns ~0.299
Kumaraswamy.prototype.quantile( p )
Evaluates the quantile function at probability p
.
var kumaraswamy = new Kumaraswamy( 2.0, 4.0 );
var y = kumaraswamy.quantile( 0.5 );
// returns ~0.399
y = kumaraswamy.quantile( 1.9 );
// returns NaN
Examples
var Kumaraswamy = require( '@stdlib/stats/base/dists/kumaraswamy/ctor' );
var kumaraswamy = new Kumaraswamy( 2.0, 4.0 );
var mu = kumaraswamy.mean;
// returns ~0.406
var mode = kumaraswamy.mode;
// returns ~0.378
var s2 = kumaraswamy.variance;
// returns ~0.035
var y = kumaraswamy.cdf( 0.8 );
// returns ~0.983