MetropolisHastingTObservation, TProposalDistribution, TTargetDistribution Class

Metropolis-Hasting sampling algorithm.

Inheritance Hierarchy

SystemObject
  Accord.Statistics.Distributions.SamplingMetropolisHastingTObservation
    Accord.Statistics.Distributions.SamplingMetropolisHastingTObservation, TProposalDistribution
      Accord.Statistics.Distributions.SamplingMetropolisHastingTObservation, TProposalDistribution, TTargetDistribution

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

Syntax

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public class MetropolisHasting<TObservation, TProposalDistribution, TTargetDistribution> : MetropolisHasting<TObservation, TProposalDistribution>
where TProposalDistribution : Object, ISampleableDistribution<TObservation[]>
where TTargetDistribution : Object, IMultivariateDistribution<TObservation[]>

Public Class MetropolisHasting(Of TObservation, TProposalDistribution As {Object, ISampleableDistribution(Of TObservation())}, TTargetDistribution As {Object, IMultivariateDistribution(Of TObservation())})
	Inherits MetropolisHasting(Of TObservation, TProposalDistribution)

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Type Parameters

TObservation
TProposalDistribution
TTargetDistribution

The MetropolisHastingTObservation, TProposalDistribution, TTargetDistribution type exposes the following members.

Constructors

	Name	Description
	MetropolisHastingTObservation, TProposalDistribution, TTargetDistribution	Initializes a new instance of the MetropolisHastingTObservation, TProposalDistribution, TTargetDistribution class.

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Properties

	Name	Description
	AcceptanceRate	Gets the acceptance rate for the proposals generated by the proposal distribution. (Inherited from MetropolisHastingT.)
	Current	Gets the last successfully generated observation. (Inherited from MetropolisHastingT.)
	CurrentValue	Gets the log-probability of the last successfully generated sample. (Inherited from MetropolisHastingT.)
	Discard	Gets or sets how many initial samples will get discarded as part of the initial thermalization (warm-up, initialization) process. (Inherited from MetropolisHastingT.)
	LogProbabilityDensityFunction	Gets the log-probability density function of the target distribution. (Inherited from MetropolisHastingT.)
	NumberOfInputs	Gets the number of dimensions in each observation. (Inherited from MetropolisHastingT.)
	Proposal	Gets or sets the move proposal distribution. (Inherited from MetropolisHastingTObservation, TProposalDistribution.)
	RandomSource	Gets or sets a factory method to create random number generators used in this instance. (Inherited from MetropolisHastingT.)
	Target	Gets the target distribution whose samples must be generated.

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Methods

	Name	Description
	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.)
	Generate	Generates a random observation from the current distribution. (Inherited from MetropolisHastingT.)
	Generate(Int32)	Generates a random vector of observations from the current distribution. (Inherited from MetropolisHastingT.)
	Generate(Int32, T)	Generates a random vector of observations from the current distribution. (Inherited from MetropolisHastingT.)
	GetHashCode	Serves as the default hash function. (Inherited from Object.)
	GetType	Gets the Type of the current instance. (Inherited from Object.)
	Initialize(Int32, FuncT, Double, FuncT, T, T)	Initializes the algorithm. (Inherited from MetropolisHastingT.)
	Initialize(Int32, FuncTObservation, Double, TProposalDistribution)	Initializes the algorithm. (Inherited from MetropolisHastingTObservation, TProposalDistribution.)
	MemberwiseClone	Creates a shallow copy of the current Object. (Inherited from Object.)
	ToString	Returns a string that represents the current object. (Inherited from Object.)
	TryGenerate	Attempts to generate a new observation from the target distribution, storing its value in the Current property. (Inherited from MetropolisHastingT.)
	TryGenerate(T)	Attempts to generate a new observation from the target distribution, storing its value in the Current property. (Inherited from MetropolisHastingT.)
	WarmUp	Thermalizes the sample generation process, generating up to Discard samples and discarding them. This step is done automatically upon the first call to any of the Generate functions. (Inherited from MetropolisHastingT.)

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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.)

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Remarks

References:

Reference

Accord.Statistics.Distributions.Sampling Namespace

MetropolisHastingAddLanguageSpecificTextSet("LST79B5A2F3_0?cs=&lt;|vb=(Of |cpp=&lt;|fs=&lt;'|nu=(");TObservation, TProposalDistribution, TTargetDistributionAddLanguageSpecificTextSet("LST79B5A2F3_1?cs=&gt;|vb=)|cpp=&gt;|fs=&gt;|nu=)"); Class

Type Parameters

Reference

MetropolisHastingTObservation, TProposalDistribution, TTargetDistribution Class