edu.ucla.stat.SOCR.distributions
Class VonMisesDistribution

java.lang.Object
  extended by edu.ucla.stat.SOCR.core.SOCRValueSettable
      extended by edu.ucla.stat.SOCR.core.Distribution
          extended by 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()