Package edu.cmu.tetrad.sem

Class EmpiricalCdf

java.lang.Object

edu.cmu.tetrad.sem.EmpiricalCdf

All Implemented Interfaces:

org.apache.commons.math3.distribution.RealDistribution

public class EmpiricalCdf
extends Object
implements org.apache.commons.math3.distribution.RealDistribution

Only the cumulativeProbability, density, setShift methods are implemented.

Version:

$Id: $Id

Author:

josephramsey

Constructor Summary

Constructors

Constructor	Description
EmpiricalCdf(List<Double> data)	Constructor for EmpiricalCdf.

Method Summary

Modifier and Type	Method	Description
double	cumulativeProbability(double x)	Calculates the cumulative probability of a given point.
double	cumulativeProbability(double v, double v1)	Deprecated. This method is deprecated and will be removed in a future release.
double	density(double v)	Calculates the probability density function (PDF) of a given point.
double	getNumericalMean()	Returns the numerical mean of the empirical cumulative distribution function (CDF).
double	getNumericalVariance()	Returns the numerical variance of the empirical cumulative distribution function (CDF).
double	getSupportLowerBound()	Returns the lower bound of the support for the distribution.
double	getSupportUpperBound()	Returns the upper bound of the support for the distribution.
double	inverseCumulativeProbability(double v)	Calculates the inverse cumulative probability of a given point.
boolean	isSupportConnected()	Returns a boolean indicating whether the support of the distribution is connected or not.
boolean	isSupportLowerBoundInclusive()	Deprecated. This method is deprecated and will be removed in a future release.
boolean	isSupportUpperBoundInclusive()	Deprecated. This method is deprecated and will be removed in a future release.
double	probability(double v)	Calculates the probability mass function (PMF) of a given point.
void	reseedRandomGenerator(long l)	Reseeds the random number generator used by the empirical cumulative distribution function (CDF).
double	sample()	Returns a sample from the empirical cumulative distribution function (CDF).
double[]	sample(int i)	Returns a sample from the empirical cumulative distribution function (CDF).

Methods inherited from class java.lang.Object

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

Constructor Details

EmpiricalCdf

public EmpiricalCdf(List<Double> data)

Constructor for EmpiricalCdf.

Parameters:

data - a List object

Method Details

cumulativeProbability

public double cumulativeProbability(double x)

Calculates the cumulative probability of a given point.

Specified by:

cumulativeProbability in interface org.apache.commons.math3.distribution.RealDistribution

Parameters:

x - the point at which the cumulative probability is evaluated

Returns:

the cumulative probability at the given point

probability

public double probability(double v)

Calculates the probability mass function (PMF) of a given point.

Specified by:

probability in interface org.apache.commons.math3.distribution.RealDistribution

Parameters:

v - the point at which the PMF is evaluated

Returns:

the probability mass function at the given point

density

public double density(double v)

Calculates the probability density function (PDF) of a given point.

Specified by:

density in interface org.apache.commons.math3.distribution.RealDistribution

Parameters:

v - the point at which the PDF is evaluated

Returns:

the probability density function at the given point

cumulativeProbability

@Deprecated
public double cumulativeProbability(double v,
 double v1)
                             throws org.apache.commons.math3.exception.NumberIsTooLargeException

Deprecated.

This method is deprecated and will be removed in a future release.

Calculates the cumulative probability of a given point within the range [v, v1].

Specified by:

cumulativeProbability in interface org.apache.commons.math3.distribution.RealDistribution

Parameters:

v - the exclusive lower bound

v1 - the inclusive upper bound

Returns:

the cumulative probability of the given point within the range

Throws:

org.apache.commons.math3.exception.NumberIsTooLargeException - if v is greater than v1

inverseCumulativeProbability

public double inverseCumulativeProbability(double v)
                                    throws org.apache.commons.math3.exception.OutOfRangeException

Calculates the inverse cumulative probability of a given point.

Specified by:

inverseCumulativeProbability in interface org.apache.commons.math3.distribution.RealDistribution

Parameters:

v - the cumulative probability

Returns:

the point at which the inverse cumulative probability is evaluated

Throws:

org.apache.commons.math3.exception.OutOfRangeException - if the cumulative probability is out of range

getNumericalMean

public double getNumericalMean()

Returns the numerical mean of the empirical cumulative distribution function (CDF). The numerical mean is calculated as the average of the data points.

Specified by:

getNumericalMean in interface org.apache.commons.math3.distribution.RealDistribution

Returns:

the numerical mean of the CDF

getNumericalVariance

public double getNumericalVariance()

Returns the numerical variance of the empirical cumulative distribution function (CDF). The numerical variance is calculated as the average of the squared differences between each data point and the numerical mean.

Specified by:

getNumericalVariance in interface org.apache.commons.math3.distribution.RealDistribution

Returns:

the numerical variance of the CDF

getSupportLowerBound

public double getSupportLowerBound()

Returns the lower bound of the support for the distribution. The support is the range of values for which the distribution is defined.

Specified by:

getSupportLowerBound in interface org.apache.commons.math3.distribution.RealDistribution

Returns:

the lower bound of the support

getSupportUpperBound

public double getSupportUpperBound()

Returns the upper bound of the support for the distribution. The support is the range of values for which the distribution is defined.

Specified by:

getSupportUpperBound in interface org.apache.commons.math3.distribution.RealDistribution

Returns:

the upper bound of the support

isSupportLowerBoundInclusive

@Deprecated
public boolean isSupportLowerBoundInclusive()

Deprecated.

This method is deprecated and will be removed in a future release.

Returns a boolean indicating whether the lower bound of the support is inclusive or not.

Specified by:

isSupportLowerBoundInclusive in interface org.apache.commons.math3.distribution.RealDistribution

Returns:

true if the lower bound is inclusive, false otherwise

isSupportUpperBoundInclusive

@Deprecated
public boolean isSupportUpperBoundInclusive()

Deprecated.

This method is deprecated and will be removed in a future release.

Returns a boolean indicating whether the upper bound of the support is inclusive or not.

Specified by:

isSupportUpperBoundInclusive in interface org.apache.commons.math3.distribution.RealDistribution

Returns:

true if the upper bound is inclusive, false otherwise

isSupportConnected

public boolean isSupportConnected()

Returns a boolean indicating whether the support of the distribution is connected or not.

Specified by:

isSupportConnected in interface org.apache.commons.math3.distribution.RealDistribution

Returns:

true if the support is connected, false otherwise

reseedRandomGenerator

public void reseedRandomGenerator(long l)

Reseeds the random number generator used by the empirical cumulative distribution function (CDF).

Specified by:

reseedRandomGenerator in interface org.apache.commons.math3.distribution.RealDistribution

Parameters:

l - the new seed value for the random number generator

sample

public double sample()

Returns a sample from the empirical cumulative distribution function (CDF).

Specified by:

sample in interface org.apache.commons.math3.distribution.RealDistribution

Returns:

a sample from the CDF

sample

public double[] sample(int i)

Returns a sample from the empirical cumulative distribution function (CDF).

Specified by:

sample in interface org.apache.commons.math3.distribution.RealDistribution

Parameters:

i - the number of random values to generate

Returns:

an array of random values sampled from the CDF