﻿ Independent(TDistribution, TObservation, TOptions) Methods

Methods
NameDescription
Clone
Creates a new object that is a copy of the current instance.
(Inherited from IndependentTDistribution, TObservation.)
ComplementaryDistributionFunction(TObservation)
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 IndependentTDistribution, TObservation.)
ComplementaryDistributionFunction(Double)
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(TObservation)
Gets the cumulative distribution function (cdf) for this distribution evaluated at point x.
(Inherited from IndependentTDistribution, TObservation.)
DistributionFunction(Double)
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(TObservation)
Fits the underlying distribution to a given set of observations.
(Inherited from IndependentTDistribution, TObservation.)
Fit(Double)
Fits the underlying distribution to a given set of observations.
(Inherited from MultivariateContinuousDistribution.)
Fit(TObservation, Double)
Fits the underlying distribution to a given set of observations.
(Inherited from IndependentTDistribution, TObservation.)
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 IndependentTDistribution.)
Fit(Double, Double, IndependentOptions)
Fits the underlying distribution to a given set of observations.
(Inherited from IndependentTDistribution.)
Fit(TObservation, Double, IndependentOptions)
Fits the underlying distribution to a given set of observations.
(Inherited from IndependentTDistribution, TObservation.)
Fit(TObservation, Double, IndependentOptionsTOptions)
Fits the underlying distribution to a given set of observations.
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(TObservation)
Generates a random observation from the current distribution.
(Inherited from IndependentTDistribution, TObservation.)
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(Int32, TObservation)
Generates a random vector of observations from the current distribution.
(Inherited from IndependentTDistribution, TObservation.)
Generate(TObservation, Random)
Generates a random observation from the current distribution.
(Inherited from IndependentTDistribution, TObservation.)
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, Double, Random)
Generates a random vector of observations from the current distribution.
(Inherited from IndependentTDistribution.)
Generate(Int32, TObservation, Random)
Generates a random vector of observations from the current distribution.
(Inherited from IndependentTDistribution, TObservation.)
Generate(Int32, Int32, Random)
Generates a random vector of observations from the current distribution.
(Inherited from MultivariateContinuousDistribution.)
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
Gets the probability density function (pdf) for this distribution evaluated at point x.
(Inherited from IndependentTDistribution.)
InnerLogProbabilityDensityFunction
Gets the log-probability density function (pdf) for this distribution evaluated at point x.
(Inherited from IndependentTDistribution.)
InnerProbabilityDensityFunction
Gets the probability density function (pdf) for this distribution evaluated at point x.
(Inherited from IndependentTDistribution.)
LogProbabilityDensityFunction
Gets the log-probability density function (pdf) for this distribution evaluated at point x.
(Inherited from MultivariateContinuousDistribution.)
LogProbabilityFunction
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 IndependentTDistribution, TObservation.)
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.)
ProbabilityFunction
Gets the probability density function (pdf) for this distribution evaluated at point x.
(Inherited from IndependentTDistribution, TObservation.)
Reset
Resets cached values (should be called after re-estimation).
(Inherited from IndependentTDistribution.)
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.
(Inherited from IndependentTDistribution.)
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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.)