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IndependentTDistribution, TObservation Methods

The IndependentTDistribution, TObservation generic type exposes the following members.

Methods
  NameDescription
Public methodClone
Creates a new object that is a copy of the current instance.
(Overrides IndependentTDistributionClone.)
Public methodComplementaryDistributionFunction(TObservation)
Gets the complementary cumulative distribution function (ccdf) for this distribution evaluated at point x. This function is also known as the Survival function.
Public methodComplementaryDistributionFunction(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.)
Public methodDistributionFunction(TObservation)
Gets the cumulative distribution function (cdf) for this distribution evaluated at point x.
Public methodDistributionFunction(Double)
Gets the probability density function (pdf) for this distribution evaluated at point x.
(Inherited from MultivariateContinuousDistribution.)
Public methodEquals
Determines whether the specified object is equal to the current object.
(Inherited from Object.)
Protected methodFinalize
Allows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection.
(Inherited from Object.)
Public methodCode exampleFit(TObservation)
Fits the underlying distribution to a given set of observations.
Public methodFit(Double)
Fits the underlying distribution to a given set of observations.
(Inherited from MultivariateContinuousDistribution.)
Public methodCode exampleFit(TObservation, Double)
Fits the underlying distribution to a given set of observations.
Public methodFit(Double, IFittingOptions)
Fits the underlying distribution to a given set of observations.
(Inherited from MultivariateContinuousDistribution.)
Public methodFit(Double, Double)
Fits the underlying distribution to a given set of observations.
(Inherited from MultivariateContinuousDistribution.)
Public methodFit(Double, Int32)
Fits the underlying distribution to a given set of observations.
(Inherited from MultivariateContinuousDistribution.)
Public methodCode exampleFit(Double, Double, IFittingOptions)
Fits the underlying distribution to a given set of observations.
(Inherited from IndependentTDistribution.)
Public methodCode exampleFit(Double, Double, IndependentOptions)
Fits the underlying distribution to a given set of observations.
(Inherited from IndependentTDistribution.)
Public methodCode exampleFit(TObservation, Double, IndependentOptions)
Fits the underlying distribution to a given set of observations.
Public methodFit(Double, Int32, IFittingOptions)
Fits the underlying distribution to a given set of observations.
(Inherited from MultivariateContinuousDistribution.)
Public methodGenerate
Generates a random observation from the current distribution.
(Inherited from MultivariateContinuousDistribution.)
Public methodGenerate(TObservation)
Generates a random observation from the current distribution.
Public methodGenerate(Double)
Generates a random observation from the current distribution.
(Inherited from MultivariateContinuousDistribution.)
Public methodGenerate(Int32)
Generates a random vector of observations from the current distribution.
(Inherited from MultivariateContinuousDistribution.)
Public methodGenerate(Int32)
Generates a random observation from the current distribution.
(Inherited from MultivariateContinuousDistribution.)
Public methodGenerate(Random)
Generates a random observation from the current distribution.
(Inherited from MultivariateContinuousDistribution.)
Public methodGenerate(Int32, TObservation)
Generates a random vector of observations from the current distribution.
Public methodGenerate(TObservation, Random)
Generates a random observation from the current distribution.
Public methodGenerate(Double, Random)
Generates a random observation from the current distribution.
(Inherited from MultivariateContinuousDistribution.)
Public methodGenerate(Int32, Double)
Generates a random vector of observations from the current distribution.
(Inherited from MultivariateContinuousDistribution.)
Public methodGenerate(Int32, Int32)
Generates a random vector of observations from the current distribution.
(Inherited from MultivariateContinuousDistribution.)
Public methodGenerate(Int32, Random)
Generates a random vector of observations from the current distribution.
(Inherited from MultivariateContinuousDistribution.)
Public methodGenerate(Int32, Random)
Generates a random observation from the current distribution.
(Inherited from MultivariateContinuousDistribution.)
Public methodGenerate(Int32, Double, Random)
Generates a random vector of observations from the current distribution.
(Inherited from IndependentTDistribution.)
Public methodGenerate(Int32, TObservation, Random)
Generates a random vector of observations from the current distribution.
Public methodGenerate(Int32, Int32, Random)
Generates a random vector of observations from the current distribution.
(Inherited from MultivariateContinuousDistribution.)
Public methodGetHashCode
Serves as the default hash function.
(Inherited from Object.)
Public methodGetType
Gets the Type of the current instance.
(Inherited from Object.)
Protected methodInnerComplementaryDistributionFunction
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.)
Protected methodInnerDistributionFunction
Gets the probability density function (pdf) for this distribution evaluated at point x.
(Inherited from IndependentTDistribution.)
Protected methodInnerLogProbabilityDensityFunction
Gets the log-probability density function (pdf) for this distribution evaluated at point x.
(Inherited from IndependentTDistribution.)
Protected methodInnerProbabilityDensityFunction
Gets the probability density function (pdf) for this distribution evaluated at point x.
(Inherited from IndependentTDistribution.)
Public methodLogProbabilityDensityFunction
Gets the log-probability density function (pdf) for this distribution evaluated at point x.
(Inherited from MultivariateContinuousDistribution.)
Public methodLogProbabilityFunction
Gets the complementary cumulative distribution function (ccdf) for this distribution evaluated at point x. This function is also known as the Survival function.
Protected methodMemberwiseClone
Creates a shallow copy of the current Object.
(Inherited from Object.)
Public methodProbabilityDensityFunction
Gets the probability density function (pdf) for this distribution evaluated at point x.
(Inherited from MultivariateContinuousDistribution.)
Public methodProbabilityFunction
Gets the probability density function (pdf) for this distribution evaluated at point x.
Protected methodReset
Resets cached values (should be called after re-estimation).
(Inherited from IndependentTDistribution.)
Public methodToString
Returns a String that represents this instance.
(Inherited from DistributionBase.)
Public methodToString(IFormatProvider)
Returns a String that represents this instance.
(Inherited from DistributionBase.)
Public methodToString(String)
Returns a String that represents this instance.
(Inherited from DistributionBase.)
Public methodToString(String, IFormatProvider)
Returns a String that represents this instance.
(Inherited from IndependentTDistribution.)
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Extension Methods
  NameDescription
Public Extension MethodHasMethod
Checks whether an object implements a method with the given name.
(Defined by ExtensionMethods.)
Public Extension MethodIsEqual
Compares two objects for equality, performing an elementwise comparison if the elements are vectors or matrices.
(Defined by Matrix.)
Public Extension MethodTo(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.)
Public Extension MethodToTOverloaded.
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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See Also