edu.ucla.stat.SOCR.distributions
Class VonMisesDistribution

java.lang.Object
  edu.ucla.stat.SOCR.core.SOCRValueSettable
      edu.ucla.stat.SOCR.core.Distribution
          edu.ucla.stat.SOCR.distributions.VonMisesDistribution

All Implemented Interfaces:

IValueSettable, Pluginable, java.util.Observer

public class VonMisesDistribution
extends Distribution

This class models the Von-Mises (Circular Gaussian) distribution on [-Pi; Pi]. http://mathworld.wolfram.com/vonMisesDistribution.html .

Field Summary

Fields inherited from class edu.ucla.stat.SOCR.core.Distribution

applet, CONTINUOUS, DISCRETE, MAXMGFXVAL, MAXMGFYVAL, MINMGFXVAL, MIXED, name

Constructor Summary

VonMisesDistribution()
This default constructor creates a new Von Mises distribuiton on (0, 1).

VonMisesDistribution(double mu, double k)
This general constructor creates a new Von Mises distribution on a specified interval.

Method Summary

double	getDensity(double x) This method computes the density function.
double	getK()
double	getMaxDensity() This method computes the maximum value of the getDensity function.
double	getMaxValue() This method returns the maximum value.
double	getMean() This method computes the mean.
double	getMinValue() This method gets the minimum value.
java.lang.String	getOnlineDescription() This method returns an online description of this distribution.
double	getSD() This method computes the Standard Diviation
double	getVariance() This method computes the variance.
double	I0(double x) This method Calls the Bessel Function defined in edu.ucla.stat.SOCR.util.BesselFunction
double	I1(double x) This method Calls the Bessel Function defined in edu.ucla.stat.SOCR.util.BesselFunction
void	initialize() used for some subclass to initialize before being used
void	paramEstimate(double[] distData)
void	setParameters(double mu, double k) This method sets the parameters: the minimum and maximum values of the interval.
void	valueChanged(java.util.Observable o, java.lang.Object arg)

Methods inherited from class edu.ucla.stat.SOCR.core.Distribution

addObserver, betaCDF, comb, factorial, findGFRoot, findRoot, gamma, gammaCDF, getCDF, getDisplayPane, getDomain, getFailureRate, getGFDerivative, getGFSecondDerivative, getInstance, getLocalHelp, getMean, getMedian, getMGF, getMgfDomain, getName, getPGF, getPGFDomain, getQuantile, getSampleMoment, getSOCRDistributionFunctors, getSOCRDistributions, getType, getVariance, inverseCDF, logGamma, perm, sampleMean, sampleVar, setApplet, setDomain, setDomain, setMGFDomain, setMGFDomain, setMGFParameters, setMGFParameters, setMGFParameters, setMGFParameters, setParameters, setPGFDomain, setPGFDomain, setPGFParameters, setPGFParameters, setPGFParameters, setPGFParameters, simulate, update, valueChanged

Methods inherited from class edu.ucla.stat.SOCR.core.SOCRValueSettable

createComponentSetter, createValueSetter, createValueSetter, createValueSetter, createValueSetter, getComponentSetter, getComponentSetters, getValueSetter, getValueSetters

Methods inherited from class java.lang.Object

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

Constructor Detail

VonMisesDistribution

public VonMisesDistribution(double mu,
                            double k)

This general constructor creates a new Von Mises distribution on a specified interval. The parameters mu and ? are mean and approximately the inverse of the variance, for large k. The distribution becomes very concentrated about the angle mu with large K. As ? increases, the distribution approaches a normal distribution in x with mean mu and variance 1/k.

VonMisesDistribution

public VonMisesDistribution()

This default constructor creates a new Von Mises distribuiton on (0, 1).

Method Detail

initialize

public void initialize()

Description copied from class: Distribution

used for some subclass to initialize before being used

Overrides:

initialize in class Distribution

valueChanged

public void valueChanged(java.util.Observable o,
                         java.lang.Object arg)

Overrides:

valueChanged in class Distribution

setParameters

public void setParameters(double mu,
                          double k)

This method sets the parameters: the minimum and maximum values of the interval.

getDensity

public double getDensity(double x)

This method computes the density function.

Specified by:

getDensity in class Distribution

getMaxDensity

public double getMaxDensity()

This method computes the maximum value of the getDensity function.

Overrides:

getMaxDensity in class Distribution

getMean

public double getMean()

This method computes the mean.

Overrides:

getMean in class Distribution

getVariance

public double getVariance()

This method computes the variance.

Overrides:

getVariance in class Distribution

I0

public double I0(double x)

This method Calls the Bessel Function defined in edu.ucla.stat.SOCR.util.BesselFunction

I1

public double I1(double x)

This method Calls the Bessel Function defined in edu.ucla.stat.SOCR.util.BesselFunction

getSD

public double getSD()

This method computes the Standard Diviation

Overrides:

getSD in class Distribution

getMinValue

public double getMinValue()

This method gets the minimum value.

getMaxValue

public double getMaxValue()

This method returns the maximum value.

getOnlineDescription

public java.lang.String getOnlineDescription()

This method returns an online description of this distribution.

Overrides:

getOnlineDescription in class Distribution

paramEstimate

public void paramEstimate(double[] distData)

Overrides:

paramEstimate in class Distribution

getK

public double getK()