﻿ GeneralDiscreteDistribution Methods   # GeneralDiscreteDistribution Methods

The GeneralDiscreteDistribution type exposes the following members. Methods
NameDescription Clone
Creates a new object that is a copy of the current instance.
(Overrides DistributionBaseClone.) ComplementaryDistributionFunction(Int32)
Gets P(X > k) the complementary cumulative distribution function (ccdf) for this distribution evaluated at point k. This function is also known as the Survival function.
(Inherited from UnivariateDiscreteDistribution.)  ComplementaryDistributionFunction(Int32, Boolean)
Gets the complementary cumulative distribution function (ccdf) for this distribution evaluated at point k. This function is also known as the Survival function.
(Inherited from UnivariateDiscreteDistribution.) CumulativeHazardFunction
Gets the cumulative hazard function for this distribution evaluated at point x.
(Inherited from UnivariateDiscreteDistribution.) DistributionFunction(Int32)
Gets P(X ≤ k), the cumulative distribution function (cdf) for this distribution evaluated at point k.
(Inherited from UnivariateDiscreteDistribution.)  DistributionFunction(Int32, Boolean)
Gets P(X ≤ k) or P(X < k), the cumulative distribution function (cdf) for this distribution evaluated at point k, depending on the value of the inclusive parameter.
(Inherited from UnivariateDiscreteDistribution.) DistributionFunction(Int32, Int32)
Gets the cumulative distribution function (cdf) for this distribution in the semi-closed interval (a; b] given as P(a < X ≤ b).
(Inherited from UnivariateDiscreteDistribution.) Equals
Determines whether the specified object is equal to the current object.
(Inherited from Object.) Fit(Double)
Fits the underlying distribution to a given set of observations. Fit(Double)
Fits the underlying distribution to a given set of observations.
(Inherited from UnivariateDiscreteDistribution.) Fit(Int32)
Fits the underlying distribution to a given set of observations.
(Inherited from UnivariateDiscreteDistribution.) Fit(Double, Double)
Fits the underlying distribution to a given set of observations. Fit(Int32, Double)
Fits the underlying distribution to a given set of observations. Fit(Double, IFittingOptions)
Fits the underlying distribution to a given set of observations.
(Inherited from UnivariateDiscreteDistribution.) Fit(Double, Double)
Fits the underlying distribution to a given set of observations.
(Inherited from UnivariateDiscreteDistribution.) Fit(Double, Int32)
Fits the underlying distribution to a given set of observations.
(Inherited from UnivariateDiscreteDistribution.) Fit(Int32, IFittingOptions)
Fits the underlying distribution to a given set of observations.
(Inherited from UnivariateDiscreteDistribution.) Fit(Double, Double, GeneralDiscreteOptions)
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 UnivariateDiscreteDistributionFit(Double, Double, IFittingOptions).) Fit(Double, Double, GeneralDiscreteOptions)
Fits the underlying distribution to a given set of observations. Fit(Int32, Double, GeneralDiscreteOptions)
Fits the underlying distribution to a given set of observations. Fit(Int32, Double, IFittingOptions)
Fits the underlying distribution to a given set of observations.
(Overrides UnivariateDiscreteDistributionFit(Int32, Double, IFittingOptions).) Fit(Double, Int32, IFittingOptions)
Fits the underlying distribution to a given set of observations.
(Inherited from UnivariateDiscreteDistribution.) Fit(Int32, Int32, IFittingOptions)
Fits the underlying distribution to a given set of observations.
(Inherited from UnivariateDiscreteDistribution.)  FromMatrix(Double, Boolean)
Creates general discrete distributions given a matrix of symbol probabilities.  FromMatrix(Double, Boolean)
Creates general discrete distributions given a matrix of symbol probabilities. Generate
Generates a random observation from the current distribution.
(Inherited from UnivariateDiscreteDistribution.) Generate(Random)
Generates a random observation from the current distribution.
(Overrides UnivariateDiscreteDistributionGenerate(Random).) Generate(Int32)
Generates a random vector of observations from the current distribution.
(Inherited from UnivariateDiscreteDistribution.) Generate(Int32, Double)
Generates a random vector of observations from the current distribution.
(Inherited from UnivariateDiscreteDistribution.) Generate(Int32, Int32)
Generates a random vector of observations from the current distribution.
(Inherited from UnivariateDiscreteDistribution.) Generate(Int32, Random)
Generates a random vector of observations from the current distribution.
(Inherited from UnivariateDiscreteDistribution.) Generate(Int32, Int32, Random)
Generates a random vector of observations from the current distribution.
(Overrides UnivariateDiscreteDistributionGenerate(Int32, Int32, Random).) Generate(Int32, Double, Random)
Generates a random vector of observations from the current distribution.
(Inherited from UnivariateDiscreteDistribution.) GetHashCode
Serves as the default hash function.
(Inherited from Object.) GetRange
Gets the distribution range within a given percentile.
(Inherited from UnivariateDiscreteDistribution.) GetType
Gets the Type of the current instance.
(Inherited from Object.) HazardFunction
Gets the hazard function, also known as the failure rate or the conditional failure density function for this distribution evaluated at point x.
(Inherited from UnivariateDiscreteDistribution.) InverseDistributionFunction
Gets the inverse of the cumulative distribution function (icdf) for this distribution evaluated at probability p. This function is also known as the Quantile function.
(Inherited from UnivariateDiscreteDistribution.) LogCumulativeHazardFunction
Gets the log-cumulative hazard function for this distribution evaluated at point x.
(Inherited from UnivariateDiscreteDistribution.) LogProbabilityMassFunction
Gets the log-probability mass function (pmf) for this distribution evaluated at point x.
(Inherited from UnivariateDiscreteDistribution.) ProbabilityMassFunction
Gets the probability mass function (pmf) for this distribution evaluated at point x.
(Inherited from UnivariateDiscreteDistribution.) QuantileDensityFunction
Gets the first derivative of the inverse distribution function (icdf) for this distribution evaluated at probability p.
(Inherited from UnivariateDiscreteDistribution.)  Random(Double, Boolean)
Returns a random symbol within the given symbol probabilities.  Random(Double, Int32)
Returns a random sample within the given symbol probabilities.  Random(Double, Int32, Random)
Returns a random sample within the given symbol probabilities.  Random(Double, Random, Boolean)
Returns a random symbol within the given symbol probabilities.  Random(Double, Int32, Int32, Boolean)
Returns a random sample within the given symbol probabilities.  Random(Double, Int32, Int32, Random, Boolean)
Returns a random sample within the given symbol probabilities. 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).)  Uniform
Constructs a new uniform discrete distribution.
Top 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.) 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.) ToTOverloaded.
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.)
Top See Also