GammaDistribution Class |
Namespace: Imsl.Stat
The GammaDistribution type exposes the following members.
Name | Description | |
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GammaDistribution | Initializes a new instance of the GammaDistribution class |
Name | Description | |
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Equals | Determines whether the specified object is equal to the current object. (Inherited from Object.) | |
Eval(Double) |
Fits a gamma probability distribution to xData and
returns the probability density at each value.
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Eval(Double, Object) |
Evaluates a gamma probability density at a given point
xData.
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Eval(Double, Object) |
Evaluates a gamma probability distribution with a given set of parameters
at each point in xData and returns the probability density at each value.
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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 a hash function for a particular type. (Inherited from Object.) | |
GetParameters |
Returns the current parameters of the gamma
probability density function.
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GetType | Gets the Type of the current instance. (Inherited from Object.) | |
MemberwiseClone | Creates a shallow copy of the current Object. (Inherited from Object.) | |
ToString | Returns a string that represents the current object. (Inherited from Object.) |
Name | Description | |
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ScaleParameter |
The maximum-likelihood estimate found for the gamma scale
parameter.
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ShapeParameter |
The maximum-likelihood estimate found for the gamma shape
parameter.
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GammaDistribution evaluates the gamma density of a given set of data, xData. If parameters are not supplied, the Eval method fits the gamma probability density function to the data by first calculating the shape and scale parameters using an MLE technique for a best fit. The gamma probability density function is defined as:
where a and b are the scale and shape parameters.The DataMining package class NaiveBayesClassifier uses GammaDistribution as a method to train continuous data.