MetropolisHastingT Class

Metropolis-Hasting sampling algorithm.

Inheritance Hierarchy

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

Syntax

public class MetropolisHasting<T> : IRandomNumberGenerator<T[]>

Public Class MetropolisHasting(Of T)
	Implements IRandomNumberGenerator(Of T())

The MetropolisHastingT type exposes the following members.

Constructors

	Name	Description
	MetropolisHastingT	Initializes a new instance of the MetropolisHastingT class.
	MetropolisHastingT(Int32, FuncT, Double, FuncT, T, T)	Initializes a new instance of the MetropolisHasting algorithm.

Properties

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

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.
	Generate(Int32)	Generates a random vector of observations from the current distribution.
	Generate(Int32, T)	Generates a random vector of observations from the current distribution.
	GetHashCode	Serves as the default hash function. (Inherited from Object.)
	GetType	Gets the Type of the current instance. (Inherited from Object.)
	Initialize	Initializes the algorithm.
	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.
	TryGenerate(T)	Attempts to generate a new observation from the target distribution, storing its value in the Current property.
	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.

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.)

Remarks

References:

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