[SerializableAttribute]
public abstract class ContinuousDistribution : Distribution

<SerializableAttribute>
Public MustInherit Class ContinuousDistribution
	Inherits Distribution

[SerializableAttribute]
public ref class ContinuousDistribution abstract : public Distribution

[<AbstractClassAttribute>]
[<SerializableAttribute>]
type ContinuousDistribution =  
    class
        inherit Distribution
    end

The ContinuousDistribution type exposes the following members.

	Name	Description
	ContinuousDistribution	Constructs a new ContinuousDistribution object.

	Name	Description
	InterQuartileRange	Returns the inter-quartile range of this distribution.
	IsSymmetrical	Gets whether the distribution is known to be symmetrical around the mean.
	Kurtosis	Gets the kurtosis of the distribution. (Inherited from Distribution.)
	Mean	Gets the mean or expectation value of the distribution. (Inherited from Distribution.)
	Skewness	Gets the skewness of the distribution. (Inherited from Distribution.)
	StandardDeviation	Gets the standard deviation of the distribution. (Inherited from Distribution.)
	StatisticSymbol	Gets the common symbol to describe a statistic from the distribution. (Inherited from Distribution.)
	Support	Gets the support of the distribution.
	Variance	Gets the variance of the distribution. (Inherited from Distribution.)

	Name	Description
	DistributionFunction	Evaluates the cumulative distribution function (CDF) of this distribution for the specified value.
	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.)
	GetExpectationValue(FuncDouble, Double)	Returns the expectation value of a function.
	GetExpectationValue(FuncDouble, Double, Double, Double)	Returns the un-normalized expectation value of a function over the specified interval.
	GetExpectedHistogram(Double, Double)	Gets a vector containing a histogram of the expected number of samples for a given total number of samples.
	GetExpectedHistogram(IntervalIndexDouble, Double)	Gets a vector containing a histogram of the expected number of samples for a given total number of samples.
	GetExpectedHistogram(Double, Double, Int32, Double)	Gets a vector whose bins contain the expected number of samples for a given total number of samples.
	GetHashCode	Serves as a hash function for a particular type. (Inherited from Object.)
	GetRandomSequence	Returns a sequence of random samples from the distribution.
	GetRandomSequence(Random)	Returns a sequence of random samples from the distribution.
	GetRandomSequence(Random, Int32)	Returns a sequence of random samples of the specified length from the distribution.
	GetRandomVariate	Obsolete. Returns a random sample from the distribution.
	GetRandomVariates(Random, Vector)	Obsolete. Fills a vector with random numbers.
	GetRandomVariates(Random, Double)	Obsolete. Fills a Double array with random numbers.
	GetRandomVariates(Random, Vector, Int32, Int32)	Obsolete. Fills a Double array with random numbers.
	GetRandomVariates(Random, Double, Int32, Int32)	Obsolete. Fills a Double array with random numbers.
	GetType	Gets the Type of the current instance. (Inherited from Object.)
	HazardFunction	Returns the probability of failure at the specified value.
	InverseDistributionFunction	Returns the inverse of the DistributionFunction(Double).
	LeftTailProbability	Returns the probability that a sample from the distribution is less than the specified value.
	LogProbabilityDensityFunction	Returns the logarithm of the probability density function (PDF) of this distribution for the specified value.
	MemberwiseClone	Creates a shallow copy of the current Object. (Inherited from Object.)
	MomentFunction	Returns the value of the moment function of the specified order.
	Probability	Returns the probability that a sample taken from the distribution lies inside the specified interval.
	ProbabilityDensityFunction	Returns the value of the probability density function (PDF) of this distribution for the specified value.
	RightTailProbability	Returns the probability that a sample from the distribution is larger than the specified value.
	Sample	Returns a random sample from the distribution.
	Sample(Int32)	Returns a vector of random samples from the distribution.
	Sample(Random)	Returns a random sample from the distribution.
	Sample(Int32, Random)	Returns a vector of random samples from the distribution.
	Sample(Random, IListDouble)	Fills a list with random numbers from the distribution.
	Sample(Random, IListDouble, Int32, Int32)	Fills part of a list with random numbers from the distribution.
	SampleInto(Random, IListDouble)	Fills a list with random numbers from the distribution.
	SampleInto(Random, IListDouble, Int32, Int32)	Fills part of a list with random numbers from the distribution.
	SurvivorDistributionFunction	Evaluates the survivor distribution function (SDF) of this distribution for the specified value.
	ToString	Returns a string that represents the current object. (Inherited from Object.)
	TwoTailedProbability	Returns the probability that a sample from the distribution deviates from the mean more than the specified value.

The distribution of a variable is a description of the relative numbers of times each possible outcome will occur in a number of trials. The function describing the distribution is called the probability function, and the function describing the cumulative probability that a given value or any value smaller than it will occur is called the distribution function.

A continuous probability distribution is a statistical distribution whose variables can take on any value within a certain interval. This interval may be infinite.

This library contains classes for the most common continuous distributions. They are listed in the table below:

ContinuousDistribution is an abstract base class that cannot be instantiated. To create a continuous distribution of a specific type, instantiate a class derived from ContinuousDistribution.

Notes to inheritors: When you inherit from ContinuousDistribution, you must override the following members: ProbabilityDensityFunction(Double), DistributionFunction(Double), Mean and Variance. You should also override the following methods: Sample, Skewness, Kurtosis.

Numerical Libraries

Reference