Package org.drip.measure.continuous

Class R1UnivariateUniform

java.lang.Object

org.drip.measure.continuous.R1Univariate

org.drip.measure.continuous.R1UnivariateUniform

public class R1UnivariateUniform
extends R1Univariate

R1UnivariateUniform implements the Univariate R¹ Uniform Distribution. It implements the Incremental, the Cumulative, and the Inverse Cumulative Distribution Densities.

• Module = Computational Core Module
• Library = Numerical Analysis Library
• Project = R^d Continuous/Discrete Probability Measures
• Package = R¹ and R^d Continuous Random Measure

Author:

Lakshmi Krishnamurthy

Constructor Summary

Constructors

Constructor	Description
R1UnivariateUniform(double leftSupport, double rightSupport)	R1UnivariateUniform Constructor

Method Summary

Modifier and Type	Method	Description
double	cumulative(double x)	Compute the cumulative under the distribution to the given value
double	density(double x)	Compute the Density under the Distribution at the given Variate
Array2D	histogram()	Retrieve the Univariate Weighted Histogram
double	incremental(double xLeft, double xRight)	Compute the Incremental under the Distribution between the 2 variates
double	invCumulative(double y)	Compute the inverse cumulative under the distribution corresponding to the given value
double	leftSupport()	Retrieve the Left Support
double	mean()	Retrieve the Mean of the Distribution
double	random()	Generate a Random Variable corresponding to the Distribution
double	rightSupport()	Retrieve the Right Support
static R1UnivariateUniform	Standard()	Construct a Standard (0, 1) R1 Univariate Uniform Distribution
double[]	support()	Lay out the Support of the PDF Range
boolean	supported(double x)	Indicate if the specified x Value stays inside the Support
double	variance()	Retrieve the Variance of the Distribution

Methods inherited from class org.drip.measure.continuous.R1Univariate

bPOE, centralMoment, cvar, differentialEntropy, excessKurtosis, expectedShortfall, fisherInformation, iqr, kullbackLeiblerDivergence, median, mode, momentGeneratingFunction, nonCentralMoment, populationCentralMeasures, probabilityGeneratingFunction, quantile, randomArray, skewness, tukeyAnomaly, tukeyCriterion

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Details

R1UnivariateUniform

public R1UnivariateUniform(double leftSupport,
double rightSupport)
                    throws java.lang.Exception

R1UnivariateUniform Constructor

Parameters:

leftSupport - The Left Support

rightSupport - The Right Support

Throws:

java.lang.Exception - Thrown if the Inputs are Invalid

Method Details

Standard

public static final R1UnivariateUniform Standard()

Construct a Standard (0, 1) R¹ Univariate Uniform Distribution

Returns:

Standard (0, 1) R¹ Univariate Uniform Distribution

leftSupport

public double leftSupport()

Retrieve the Left Support

Returns:

The Left Support

rightSupport

public double rightSupport()

Retrieve the Right Support

Returns:

The Right Support

supported

public boolean supported(double x)

Indicate if the specified x Value stays inside the Support

Overrides:

supported in class R1Univariate

Parameters:

x - X

Returns:

The Value stays in Support

support

public double[] support()

Description copied from class: R1Univariate

Lay out the Support of the PDF Range

Specified by:

support in class R1Univariate

Returns:

Support of the PDF Range

cumulative

public double cumulative(double x)
                  throws java.lang.Exception

Description copied from class: R1Univariate

Compute the cumulative under the distribution to the given value

Specified by:

cumulative in class R1Univariate

Parameters:

x - Variate to which the cumulative is to be computed

Returns:

The cumulative

Throws:

java.lang.Exception - Thrown if the inputs are invalid

incremental

public double incremental(double xLeft,
double xRight)
                   throws java.lang.Exception

Description copied from class: R1Univariate

Compute the Incremental under the Distribution between the 2 variates

Overrides:

incremental in class R1Univariate

Parameters:

xLeft - Left Variate to which the cumulative is to be computed

xRight - Right Variate to which the cumulative is to be computed

Returns:

The Incremental under the Distribution between the 2 variates

Throws:

java.lang.Exception - Thrown if the inputs are invalid

invCumulative

public double invCumulative(double y)
                     throws java.lang.Exception

Description copied from class: R1Univariate

Compute the inverse cumulative under the distribution corresponding to the given value

Overrides:

invCumulative in class R1Univariate

Parameters:

y - Value corresponding to which the inverse cumulative is to be computed

Returns:

The inverse cumulative

Throws:

java.lang.Exception - Thrown if the Input is invalid

density

public double density(double x)
               throws java.lang.Exception

Description copied from class: R1Univariate

Compute the Density under the Distribution at the given Variate

Specified by:

density in class R1Univariate

Parameters:

x - Variate at which the Density needs to be computed

Returns:

The Density

Throws:

java.lang.Exception - Thrown if the input is invalid

mean

public double mean()

Description copied from class: R1Univariate

Retrieve the Mean of the Distribution

Specified by:

mean in class R1Univariate

Returns:

The Mean of the Distribution

variance

public double variance()

Description copied from class: R1Univariate

Retrieve the Variance of the Distribution

Specified by:

variance in class R1Univariate

Returns:

The Variance of the Distribution

random

public double random()

Description copied from class: R1Univariate

Generate a Random Variable corresponding to the Distribution

Overrides:

random in class R1Univariate

Returns:

Random Variable corresponding to the Distribution

histogram

public Array2D histogram()

Description copied from class: R1Univariate

Retrieve the Univariate Weighted Histogram

Overrides:

histogram in class R1Univariate

Returns:

The Univariate Weighted Histogram