DiscreteDistribution

References
[IoId("00000000-35D9-4AC9-B5EA-A9AA2235396A")] public struct DiscreteDistribution : IStorable
Represents a variety of discrete statistical distributions.

Constructors

DiscreteDistribution

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public DiscreteDistribution(IReader reader)
Parameters:
reader (IReader)

Properties

Deviation

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public double Deviation { get; }
Gets the standard deviation of this distribution. Not all types of distribution have a meaningful deviation, in which case this property returns NaN.

Entropy

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public double Entropy { get; }
Gets the entropy of this distribution. Not all types of distribution have an entropy value, in which case this property returns NaN.

Maximum

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public int Maximum { get; }
Gets the largest parameter for which this distribution is defined.

Mean

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public double Mean { get; }
Gets the mean of this distribution. Not all types of distribution have a mean, in which case this property returns NaN.

Median

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public double Median { get; }
Gets the median of this distribution. Not all types of distribution have a median, in which case this property returns NaN.

Minimum

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public int Minimum { get; }
Gets the smallest parameter for which this distribution is defined.

Mode

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public int Mode { get; }
Gets the mode of this distribution. Not all types of distribution have a mode, in which case this property returns NaN.

Skewness

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public double Skewness { get; }
Gets the statistical skewness of this distribution. Not all types of distribution have a skewness, in which case this property returns NaN.

Type

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public DistributionType Type { get; }
Gets the type of this distribution.

Variance

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public double Variance { get; }
Gets the statistical variance of this distribution. Not all types of distribution have a variance, in which case this property returns NaN.

Methods

CreateBernoulli

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public static DiscreteDistribution CreateBernoulli(double p)
Create a Bernoulli discrete distribution.
Parameters:
p (double)Chance of success (0, 1).

CreateBinomial

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public static DiscreteDistribution CreateBinomial(double p, int n)
Create a Binomial discrete distribution.
Parameters:
p (double)
n (int)

CreateConwayMaxwell

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public static DiscreteDistribution CreateConwayMaxwell(double lambda, double nu)
Create a Conway-Maxwell-Poisson discrete distribution.
Parameters:
lambda (double)
nu (double)

CreateGeometric

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public static DiscreteDistribution CreateGeometric(double p)
Create a Geometric discrete distribution.
Parameters:
p (double)

CreateHyperGeometric

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public static DiscreteDistribution CreateHyperGeometric(int population, int success, int draws)
Create a Hyper-Geometric discrete distribution.
Parameters:
population (int)
success (int)
draws (int)

CreatePoisson

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public static DiscreteDistribution CreatePoisson(double lambda)
Create a Poisson discrete distribution.
Parameters:
lambda (double)

CreateSampling

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public int[] CreateSampling(Random random, int count)
Gets a collection of random samples within this distribution. This method should only be called when the distribution is discrete.
Parameters:
random (Random)Random engine.
count (int)Number of samples.
Returns: Array of samples.

CreateSamplingConsistent

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public int[] CreateSamplingConsistent(RandomEngine engine, int count)
Create a random sampling of this distribution which is more consistent but slower than the CreateSampling(Random, int) method.
Parameters:
engine (RandomEngine)Random engine to use.
count (int)Number of samples to create.

CreateUniform

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public static DiscreteDistribution CreateUniform(int minimum, int maximum)
Create a uniform discrete distribution.
Parameters:
minimum (int)Start of distribution (inclusive).
maximum (int)End of distribution (includive).

CreateZipf

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public static DiscreteDistribution CreateZipf(double shape, int n)
Create a Zipf discrete distribution.
Parameters:
shape (double)
n (int)

CumulativeAt

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public double CumulativeAt(double x)
Gets the cumulative distribution at x.
Parameters:
x (double)Parameter.
Returns: Cumulative probability at x.

GetPreview

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public void GetPreview(out int[] i, out double[] pdf, out double[] cdf)
Create a preview of the PDF and CDF functions.
Parameters:
i (out int[])Sample indices.
pdf (out double[])Value of the PDF at every sample.
cdf (out double[])Value of the CDF at every sample.

GetRelevantInterval

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public (int i0, int i1) GetRelevantInterval()
Gets the relevant x-interval in which the distribution has the most detailed progression. This method is used to decide on which interval any distribution previews ought to be drawn.

ProbabilityAt

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public double ProbabilityAt(int i)
Gets the probability density of the distribution at index i.
Parameters:
i (int)Parameter.
Returns: Probability density at i.

Store

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public void Store(IWriter writer)
Parameters:
writer (IWriter)
Implements: Store

ToString

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public override string ToString()
Overrides: ValueType.ToString

ValidateConwayMaxwellNuParameter

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public static double ValidateConwayMaxwellNuParameter(double lambda, double nu)
Parameters:
lambda (double)
nu (double)