﻿ HiddenMarkovDistribution Methods

# HiddenMarkovDistribution Methods

The HiddenMarkovDistribution type exposes the following members.

Methods
NameDescription
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 MultivariateDiscreteDistribution.)
DistributionFunction
Gets the cumulative distribution function (cdf) for this distribution evaluated at point x.
(Inherited from MultivariateDiscreteDistribution.)
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 MultivariateDiscreteDistribution.)
Fit(Double, IFittingOptions)
Fits the underlying distribution to a given set of observations.
(Inherited from MultivariateDiscreteDistribution.)
Fit(Double, Double)
Fits the underlying distribution to a given set of observations.
(Inherited from MultivariateDiscreteDistribution.)
Fit(Double, Int32)
Fits the underlying distribution to a given set of observations.
(Inherited from MultivariateDiscreteDistribution.)
Fit(Double, Double, HiddenMarkovOptions)
Fits the underlying distribution to a given set of observations.
Fit(Double, Double, IFittingOptions)
Fits the underlying distribution to a given set of observations.
(Overrides MultivariateDiscreteDistributionFit(Double, Double, IFittingOptions).)
Fit(Double, Int32, IFittingOptions)
Fits the underlying distribution to a given set of observations.
(Inherited from MultivariateDiscreteDistribution.)
Generate
Generates a random observation from the current distribution.
(Inherited from MultivariateDiscreteDistribution.)
Generate(Double)
Generates a random observation from the current distribution.
(Inherited from MultivariateDiscreteDistribution.)
Generate(Int32)
Generates a random vector of observations from the current distribution.
(Inherited from MultivariateDiscreteDistribution.)
Generate(Int32)
Generates a random observation from the current distribution.
(Inherited from MultivariateDiscreteDistribution.)
Generate(Random)
Generates a random observation from the current distribution.
(Inherited from MultivariateDiscreteDistribution.)
Generate(Double, Random)
Generates a random observation from the current distribution.
(Inherited from MultivariateDiscreteDistribution.)
Generate(Int32, Double)
Generates a random vector of observations from the current distribution.
(Inherited from MultivariateDiscreteDistribution.)
Generate(Int32, Int32)
Generates a random vector of observations from the current distribution.
(Inherited from MultivariateDiscreteDistribution.)
Generate(Int32, Random)
Generates a random vector of observations from the current distribution.
(Inherited from MultivariateDiscreteDistribution.)
Generate(Int32, Random)
Generates a random observation from the current distribution.
(Inherited from MultivariateDiscreteDistribution.)
Generate(Int32, Double, Random)
Generates a random vector of observations from the current distribution.
(Inherited from MultivariateDiscreteDistribution.)
Generate(Int32, Int32, Random)
Generates a random vector of observations from the current distribution.
(Inherited from MultivariateDiscreteDistribution.)
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 MultivariateDiscreteDistribution.)
InnerDistributionFunction
Gets the cumulative distribution function (cdf) for this distribution evaluated at point x.
(Overrides MultivariateDiscreteDistributionInnerDistributionFunction(Int32).)
InnerInverseDistributionFunction
Not supported.
(Inherited from MultivariateDiscreteDistribution.)
InnerLogProbabilityMassFunction
Gets the log-probability mass function (pmf) for this distribution evaluated at point x.
(Overrides MultivariateDiscreteDistributionInnerLogProbabilityMassFunction(Int32).)
InnerProbabilityMassFunction
Gets the probability mass function (pmf) for this distribution evaluated at point x.
(Overrides MultivariateDiscreteDistributionInnerProbabilityMassFunction(Int32).)
InverseDistributionFunction
Not supported.
(Inherited from MultivariateDiscreteDistribution.)
LogProbabilityMassFunction
Gets the log-probability mass function (pmf) for this distribution evaluated at point x.
(Inherited from MultivariateDiscreteDistribution.)
MarginalDistributionFunction(Int32)
Gets the marginal distribution of a given variable.
(Inherited from MultivariateDiscreteDistribution.)
MarginalDistributionFunction(Int32, Int32)
Gets the marginal distribution of a given variable evaluated at a given value.
(Inherited from MultivariateDiscreteDistribution.)
MemberwiseClone
Creates a shallow copy of the current Object.
(Inherited from Object.)
ProbabilityMassFunction
Gets the probability mass function (pmf) for this distribution evaluated at point x.
(Inherited from MultivariateDiscreteDistribution.)
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).)
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Extension Methods
NameDescription
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.)