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NormalDistribution Class

Generates normal (Gaussian) distributed random numbers.
Inheritance Hierarchy

Namespace: Altaxo.Calc.Probability.Old
Assembly: AltaxoCore (in AltaxoCore.dll) Version: 4.8.3179.0 (4.8.3179.0)
Syntax
C#
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public class NormalDistribution : ProbabilityDistribution

The NormalDistribution type exposes the following members.

Constructors
 NameDescription
Protected methodNormalDistributionInitializes a new instance of the NormalDistribution class
Public methodNormalDistribution(Double, Double, RandomGenerator)Initializes a new instance of the NormalDistribution class
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Properties
 NameDescription
Public propertyGeneratorReturns the random generator used by the distribution to generate the random values.
(Inherited from ProbabilityDistribution)
Public propertyMean 
Public propertyStdev 
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Methods
 NameDescription
Public methodCDF
(Overrides ProbabilityDistributionCDF(Double))
Public methodEqualsDetermines whether the specified object is equal to the current object.
(Inherited from Object)
Protected methodFinalizeAllows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection.
(Inherited from Object)
Public methodGetHashCodeServes as the default hash function.
(Inherited from Object)
Public methodGetTypeGets the Type of the current instance.
(Inherited from Object)
Protected methodMemberwiseCloneCreates a shallow copy of the current Object.
(Inherited from Object)
Public methodNextDouble
(Overrides ProbabilityDistributionNextDouble)
Public methodPDF
(Overrides ProbabilityDistributionPDF(Double))
Public methodQuantile
(Overrides ProbabilityDistributionQuantile(Double))
Public methodToStringReturns a string that represents the current object.
(Inherited from Object)
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Fields
 NameDescription
Protected fieldcached 
Protected fieldcacheval 
Protected fieldgeneratorPointer to generator.
(Inherited from ProbabilityDistribution)
Protected fieldmu 
Protected fieldscale 
Protected fieldsigma 
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Remarks
C#
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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
See Also