NormalDistribution Class

Provides generation of normal distributed random numbers.

Inheritance Hierarchy

SystemObject
  Altaxo.Calc.ProbabilityDistribution
    Altaxo.Calc.ProbabilityContinuousDistribution
      Altaxo.Calc.ProbabilityNormalDistribution

Namespace: Altaxo.Calc.Probability
Assembly: AltaxoCore (in AltaxoCore.dll) Version: 4.8.3179.0 (4.8.3179.0)

Syntax

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public class NormalDistribution : ContinuousDistribution

The NormalDistribution type exposes the following members.

Constructors

	Name	Description
	NormalDistribution	Initializes a new instance of the NormalDistribution class, using a StandardGenerator as underlying random number generator.
	NormalDistribution(Generator)	Initializes a new instance of the NormalDistribution class, using the specified Generator as underlying random number generator.
	NormalDistribution(Double, Double)	Initializes a new instance of the NormalDistribution class, using the DefaultGenerator as underlying random number generator.
	NormalDistribution(Double, Double, Generator)	Initializes a new instance of the NormalDistribution class, using the specified Generator as underlying random number generator.

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Properties

	Name	Description
	CanReset	Gets a value indicating whether the random number distribution can be reset, so that it produces the same random number sequence again. (Inherited from Distribution)
	Generator	Gets or sets a Generator object that can be used as underlying random number generator. (Inherited from Distribution)
	Maximum	Gets the maximum possible value of normal distributed random numbers. (Overrides DistributionMaximum)
	Mean	Gets the mean value of normal distributed random numbers. (Overrides DistributionMean)
	Median	Gets the median of normal distributed random numbers. (Overrides DistributionMedian)
	Minimum	Gets the minimum possible value of normal distributed random numbers. (Overrides DistributionMinimum)
	Mode	Gets the mode of normal distributed random numbers. (Overrides DistributionMode)
	Mu	Gets or sets the parameter mu which is used for generation of normal distributed random numbers.
	Sigma	Gets or sets the parameter sigma which is used for generation of normal distributed random numbers.
	Variance	Gets the variance of normal distributed random numbers. (Overrides DistributionVariance)

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Methods

	Name	Description
	CDF(Double)	(Overrides ContinuousDistributionCDF(Double))
	CDF(Double, Double, Double)
	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)
	GetHashCode	Serves as the default hash function. (Inherited from Object)
	GetType	Gets the Type of the current instance. (Inherited from Object)
	Initialize
	IsValidMu	Determines whether the specified value is valid for parameter Mu.
	IsValidSigma	Determines whether the specified value is valid for parameter Sigma.
	MemberwiseClone	Creates a shallow copy of the current Object. (Inherited from Object)
	NextDouble	Returns a normal distributed floating point random number. (Overrides DistributionNextDouble)
	PDF(Double)	(Overrides ContinuousDistributionPDF(Double))
	PDF(Double, Double, Double)
	Quantile(Double)	(Overrides ContinuousDistributionQuantile(Double))
	Quantile(Double, Double, Double)
	Reset	Resets the random number distribution, so that it produces the same random number sequence again. (Inherited from Distribution)
	ToString	Returns a string that represents the current object. (Inherited from Object)

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Fields

	Name	Description
	generator	Stores a Generator object that can be used as underlying random number generator. (Inherited from Distribution)

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Remarks

The implementation of the NormalDistribution type bases upon information presented on Wikipedia - Normal distribution and the implementation in the Communication Networks Class Library.

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Return normal (Gaussian) distributed random deviates
with mean "m" and standard deviation  "s" according to the density:

                                          2
                     1               (x-m)
 p   (x) dx =  ------------  exp( - ------- ) dx
  m,s          sqrt(2 pi) s          2 s*s

Reference

Altaxo.Calc.Probability Namespace