UniformSphereDistribution Class

Uniform distribution inside a n-dimensional ball.

Inheritance Hierarchy

SystemObject
  Accord.Statistics.DistributionsDistributionBase
    Accord.Statistics.Distributions.MultivariateMultivariateContinuousDistribution
      Accord.Statistics.Distributions.MultivariateUniformSphereDistribution

Namespace: Accord.Statistics.Distributions.Multivariate
Assembly: Accord.Statistics (in Accord.Statistics.dll) Version: 3.8.0

Syntax

Copy

[SerializableAttribute]
public class UniformSphereDistribution : MultivariateContinuousDistribution, 
	ISampleableDistribution<double[]>, IDistribution<double[]>, IDistribution, 
	ICloneable, IRandomNumberGenerator<double[]>

<SerializableAttribute>
Public Class UniformSphereDistribution
	Inherits MultivariateContinuousDistribution
	Implements ISampleableDistribution(Of Double()), IDistribution(Of Double()), 
	IDistribution, ICloneable, IRandomNumberGenerator(Of Double())

Request Example View Source

The UniformSphereDistribution type exposes the following members.

Constructors

	Name	Description
	UniformSphereDistribution(Int32)	Initializes a new instance of the UniformSphereDistribution class.
	UniformSphereDistribution(Double, Double)	Initializes a new instance of the UniformSphereDistribution class.

Top

Properties

	Name	Description
	Covariance	Gets the variance-covariance matrix for this distribution. (Overrides MultivariateContinuousDistributionCovariance.)
	Dimension	Gets the number of variables for this distribution. (Inherited from MultivariateContinuousDistribution.)
	Mean	Gets the sphere center (mean) vector. (Overrides MultivariateContinuousDistributionMean.)
	Median	Gets the median for this distribution. (Inherited from MultivariateContinuousDistribution.)
	Mode	Gets the mode for this distribution. (Inherited from MultivariateContinuousDistribution.)
	Radius	Gets the sphere radius.
	Surface	Gets the sphere volume.
	Variance	Gets the variance for this distribution. (Overrides MultivariateContinuousDistributionVariance.)

Top

Methods

	Name	Description
	Clone	Creates a new object that is a copy of the current instance. (Overrides DistributionBaseClone.)
	ComplementaryDistributionFunction	Gets the complementary cumulative distribution function (ccdf) for this distribution evaluated at point x. This function is also known as the Survival function. (Inherited from MultivariateContinuousDistribution.)
	DistributionFunction	Gets the probability density function (pdf) for this distribution evaluated at point x. (Inherited from MultivariateContinuousDistribution.)
	Equals	Determines whether the specified object is equal to the current object. (Inherited from Object.)
	Finalize	Allows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection. (Inherited from Object.)
	Fit(Double)	Fits the underlying distribution to a given set of observations. (Inherited from MultivariateContinuousDistribution.)
	Fit(Double, IFittingOptions)	Fits the underlying distribution to a given set of observations. (Inherited from MultivariateContinuousDistribution.)
	Fit(Double, Double)	Fits the underlying distribution to a given set of observations. (Inherited from MultivariateContinuousDistribution.)
	Fit(Double, Int32)	Fits the underlying distribution to a given set of observations. (Inherited from MultivariateContinuousDistribution.)
	Fit(Double, Double, IFittingOptions)	Fits the underlying distribution to a given set of observations. (Inherited from MultivariateContinuousDistribution.)
	Fit(Double, Int32, IFittingOptions)	Fits the underlying distribution to a given set of observations. (Inherited from MultivariateContinuousDistribution.)
	Generate	Generates a random observation from the current distribution. (Inherited from MultivariateContinuousDistribution.)
	Generate(Double)	Generates a random observation from the current distribution. (Inherited from MultivariateContinuousDistribution.)
	Generate(Int32)	Generates a random vector of observations from the current distribution. (Inherited from MultivariateContinuousDistribution.)
	Generate(Int32)	Generates a random observation from the current distribution. (Inherited from MultivariateContinuousDistribution.)
	Generate(Random)	Generates a random observation from the current distribution. (Inherited from MultivariateContinuousDistribution.)
	Generate(Double, Random)	Generates a random observation from the current distribution. (Inherited from MultivariateContinuousDistribution.)
	Generate(Int32, Double)	Generates a random vector of observations from the current distribution. (Inherited from MultivariateContinuousDistribution.)
	Generate(Int32, Int32)	Generates a random vector of observations from the current distribution. (Inherited from MultivariateContinuousDistribution.)
	Generate(Int32, Random)	Generates a random vector of observations from the current distribution. (Inherited from MultivariateContinuousDistribution.)
	Generate(Int32, Random)	Generates a random observation from the current distribution. (Inherited from MultivariateContinuousDistribution.)
	Generate(Int32, Int32, Random)	Generates a random vector of observations from the current distribution. (Inherited from MultivariateContinuousDistribution.)
	Generate(Int32, Double, Random)	Generates a random vector of observations from the current distribution. (Overrides MultivariateContinuousDistributionGenerate(Int32, Double, Random).)
	GetHashCode	Serves as the default hash function. (Inherited from Object.)
	GetType	Gets the Type of the current instance. (Inherited from Object.)
	InnerComplementaryDistributionFunction	Gets the complementary cumulative distribution function (ccdf) for this distribution evaluated at point x. This function is also known as the Survival function. (Inherited from MultivariateContinuousDistribution.)
	InnerDistributionFunction	Not implemented. (Overrides MultivariateContinuousDistributionInnerDistributionFunction(Double).)
	InnerLogProbabilityDensityFunction	Gets the log-probability density function (pdf) for this distribution evaluated at point x. (Overrides MultivariateContinuousDistributionInnerLogProbabilityDensityFunction(Double).)
	InnerProbabilityDensityFunction	Gets the probability density function (pdf) for this distribution evaluated at point x. (Overrides MultivariateContinuousDistributionInnerProbabilityDensityFunction(Double).)
	LogProbabilityDensityFunction	Gets the log-probability density function (pdf) for this distribution evaluated at point x. (Inherited from MultivariateContinuousDistribution.)
	MemberwiseClone	Creates a shallow copy of the current Object. (Inherited from Object.)
	ProbabilityDensityFunction	Gets the probability density function (pdf) for this distribution evaluated at point x. (Inherited from MultivariateContinuousDistribution.)
	Random(Int32, Int32)	Generates a random vector of observations from the current distribution.
	Random(Int32, Int32, Double)	Generates a random vector of observations from the current distribution.
	Random(Int32, Int32, Random)	Generates a random vector of observations from the current distribution.
	Random(Int32, Double, Double, Double)	Generates a random vector of observations from the current distribution.
	Random(Int32, Int32, Double, Random)	Generates a random vector of observations from the current distribution.
	Random(Int32, Double, Double, Double, Random)	Generates a random vector of observations from the current distribution.
	ToString	Returns a String that represents this instance. (Inherited from DistributionBase.)
	ToString(IFormatProvider)	Returns a String that represents this instance. (Inherited from DistributionBase.)
	ToString(String)	Returns a String that represents this instance. (Inherited from DistributionBase.)
	ToString(String, IFormatProvider)	Returns a String that represents this instance. (Overrides DistributionBaseToString(String, IFormatProvider).)

Top

Extension Methods

	Name	Description
	HasMethod	Checks whether an object implements a method with the given name. (Defined by ExtensionMethods.)
	IsEqual	Compares two objects for equality, performing an elementwise comparison if the elements are vectors or matrices. (Defined by Matrix.)
	To(Type)	Overloaded. Converts an object into another type, irrespective of whether the conversion can be done at compile time or not. This can be used to convert generic types to numeric types during runtime. (Defined by ExtensionMethods.)
	ToT	Overloaded. Converts an object into another type, irrespective of whether the conversion can be done at compile time or not. This can be used to convert generic types to numeric types during runtime. (Defined by ExtensionMethods.)

Top

Reference

Accord.Statistics.Distributions.Multivariate Namespace

Accord.Statistics.Distributions.MultivariateMultivariateContinuousDistribution