Uses of Class
edu.uah.math.distributions.Distribution

Packages that use Distribution
edu.uah.math.devices   
edu.uah.math.distributions   
 

Uses of Distribution in edu.uah.math.devices
 

Methods in edu.uah.math.devices that return Distribution
 Distribution QuantileTable.getDistribution()
          This method returns the distribution
 Distribution DistributionGraph.getDistribution()
          This method returns the distribution associated with the graph.
 

Methods in edu.uah.math.devices with parameters of type Distribution
 void QuantileTable.setDistribution(Distribution d)
          This method sets the distribution.
 void DistributionGraph.setDistribution(Distribution d)
          This method specifies the distribution and sets up graph paramters.
 

Constructors in edu.uah.math.devices with parameters of type Distribution
CriticalGraph(Distribution d)
          This general constructor creates a new critical graph with a specified distribution.
DistributionGraph(Distribution d)
          This general constructor creates a new distribution graph with a specified distribution.
QuantileGraph(Distribution d)
          This special constructor creates a new quantile graph that shows a specified distribution and the median (quanitle of order 0.5).
QuantileGraph(Distribution d, double x)
          This general constructor creates a new quantile graph that shows a specified distribution and quanitle.
QuantileTable(Distribution d, double[] p)
          This general constructor creates a new quantile table corresponding to a given distribution and a given array of probabilities.
QuantileTable(Distribution d, int n)
          This general constructor creates a new quantile table corresponding to a given distribution and a uniform set of probabilities.
 

Uses of Distribution in edu.uah.math.distributions
 

Subclasses of Distribution in edu.uah.math.distributions
 class BernoulliDistribution
          This class models the Bernoulli distribution with a specified parameter.
 class BetaDistribution
          This class is models the beta distribution with specified left and right parameters.
 class BinomialDistribution
          This class models the binomial distribution with a specified number of trials and probability of success.
 class BinomialRandomNDistribution
          This class models the binomial distribution with a random number of trials.
 class BirthdayDistribution
          This class models the distribution of the number of distinct sample values when a sample of a specified size is chosen with replacement from a finite population of a specified size.
 class CauchyDistribution
          This class models the Cauchy distribution.
 class ChiSquareDistribution
          This class defines the chi-square distribution with a specifed degrees of freedom parameter.
 class CircleDistribution
          This class models the crcle distribution with a specified radius.
 class ContinuousUniformDistribution
          This class models the uniform distribution on a specified interval.
 class ConvolutionDistribution
          This class creates covolution of a given distribution to a given power.
 class CouponDistribution
          This class models the distribution of the sample size needed to get a specified number of distinct sample values when sampling with replacement from a finite population of a specified size.
 class DieDistribution
          This class models the distribution for a standard 6-sided die.
 class DiscreteArcsineDistribution
          This class models the discrete arcsine distribution.
 class DiscreteUniformDistribution
          This class models the discrete uniform distribution on a finite set.
 class ExponentialDistribution
          This class defines the standard exponential distribution with a specified rate parameter.
 class ExtremeValueDistribution
          This class models the exponential-type extreme value distribution.
 class FiniteDistribution
          This class models a basic discrete distribution on a finite set of points, with specified probabilities.
 class FiniteOrderStatisticDistribution
          This class models the distribution of an order statistic for a sample chosen without replacement from {1, 2..., N} .
 class FisherDistribution
          This class models the Fisher F distribution with a spcified number of degrees of freedom in the numerator and denominator.
 class GammaDistribution
          This class models the gamma distribution with a specified shape parameter and scale parameter.
 class GeometricDistribution
          This class models the geometric distribution with a given success probability.
 class HypergeometricDistribution
          This class models the hypergeometric distribution with a specified population size, sample size, and number of type 1 objects.
 class LocationScaleDistribution
          This class applies a location-scale tranformation to a given distribution.
 class LogisticDistribution
          This class models the logistic distribution.
 class LogNormalDistribution
          This class models the lognormal distribution with specified parameters.
 class MatchDistribution
          This class models the distribution of the number of matches in a random permutation.
 class MixtureDistribution
          This class models a distributions which is the mixture of a given set of distributions using a given set of probabilities as the mixing parameters
 class NegativeBinomialDistribution
          This class models the negative binomial distribution with specified successes parameter and probability parameter.
 class NormalDistribution
          This class encapsulates the normal distribution with specified parameters.
 class OrderStatisticDistribution
          This class models the distribution of the order statistic of a specified order from a random sample of a specified size from a specified sampling distribution.
 class ParetoDistribution
          This class models the Pareto distribution with a specified parameter.
 class PoissonDistribution
          The class models the Poisson distribution with a specified rate parameter.
 class StudentDistribution
          This class models the student t distribution with a specifed degrees of freeom parameter.
 class TriangleDistribution
          This class models the triangle distribution on a specified interval.
 class WalkMaxDistribution
          This class models the distribution of the maximum value of a symmetric random walk on the interval [0, n].
 class WalkPositionDistribution
          This class models the distribution of the position at time n for a random walk on the interval [0, n].
 class WeibullDistribution
          This class models the Weibull distribution with specified shape and scale parameters.
 

Methods in edu.uah.math.distributions that return Distribution
 Distribution RandomVariable.getDistribution()
          This method gets the probability distribution.
 Distribution OrderStatisticDistribution.getDistribution()
          This method returns the sampling distribution.
 Distribution LocationScaleDistribution.getDistribution()
          This method gets the underlying distribution that is being moved and scaled.
 Distribution ConvolutionDistribution.getDistribution()
          This method returns the distribution.
 Distribution BinomialRandomNDistribution.getDistribution()
          This method gets the distribution for the number of trials.
 Distribution[] MixtureDistribution.getDistributions()
          This method returns the array of distributions.
 Distribution MixtureDistribution.getDistributions(int i)
          This method returns a particular distribution.
 

Methods in edu.uah.math.distributions with parameters of type Distribution
 void RandomVariable.setDistribution(Distribution d)
          This method assigns the probability distribution and create a corresponding interval data distribution.
 void OrderStatisticDistribution.setDistribution(Distribution d)
          This method sets the sampling distribution.
 void LocationScaleDistribution.setDistribution(Distribution d)
          This method sets the distribution to be moved and scaled.
 void ConvolutionDistribution.setDistribution(Distribution d)
          This method sets the distribution.
 void BinomialRandomNDistribution.setDistribution(Distribution d)
          This method sets the distribution for the number of trials.
 void MixtureDistribution.setDistributions(Distribution[] d)
          This method sets the distributions.
 void MixtureDistribution.setDistributions(int i, Distribution d)
          This method sets a particular distribution.
 void MixtureDistribution.setParameters(Distribution[] d, double[] p)
          This method sets up the domain of the general mixture distributions in terms of the distributions being mixed.
 void MixtureDistribution.setParameters(Distribution d0, Distribution d1, double a)
          This method sets up the domain of for the mixture of two distributions.
 void BinomialRandomNDistribution.setParameters(Distribution d, double p)
          This method sets the parameters: the distribution for the number of trials and the probability of success.
 void LocationScaleDistribution.setParameters(Distribution d, double a, double b)
          This method sets the parameters, the distribution and the location and scale parameters, and sets up the domain.
 void ConvolutionDistribution.setParameters(Distribution d, int n)
          This method sets the parameters: the distribution and convolution power.
 void OrderStatisticDistribution.setParameters(Distribution d, int n, int k)
          This method sets the parameters: the sampling distribution, sample size, and order.
 

Constructors in edu.uah.math.distributions with parameters of type Distribution
BinomialRandomNDistribution(Distribution d, double p)
          This general constructor creates a new randomized binomial distribution with a specified probability of success and a specified distribution for the number of trials.
ConvolutionDistribution(Distribution d, int n)
          This general constructor: creates a new convolution distribution corresponding to a specified distribution and convolution power.
LocationScaleDistribution(Distribution d, double a, double b)
          This general constructor creates a new location-scale transformation on a given distribuiton with given location and scale parameters.
MixtureDistribution(Distribution[] d, double[] p)
          This general constructor creates the mixture of a given array of distribuitons using a given array of probabilities as the mixing parameters.
MixtureDistribution(Distribution d0, Distribution d1)
          This special constructor creates the mixture of two distributions with equal mixing probabilities
MixtureDistribution(Distribution d0, Distribution d1, double a)
          This special constructor creates the mixture of two distributions using a specified number and its complement as the mixing probabilities.
OrderStatisticDistribution(Distribution d, int n, int k)
          This general constructor creates a new order statistic distribution corresponding to a specified sampling distribution, sample size, and order.
RandomVariable(Distribution d)
          This special constructor creates a new random variable with a specified probability distribution and the default name "X".
RandomVariable(Distribution d, java.lang.String n)
          This general constructor creates a new random variable with a specified probability distribution and name.