LogNormalDistribution Class |
Namespace: Imsl.Stat
The LogNormalDistribution type exposes the following members.
Name | Description | |
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LogNormalDistribution | Initializes a new instance of the LogNormalDistribution 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 lognormal probability distribution
to xData and returns the probability density
at each value.
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Eval(Double, Object) |
Evaluates a lognormal probability density function at a given point
xData.
| |
Eval(Double, Object) |
Evaluates a lognormal 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 lognormal probability
density function.
| |
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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Mean |
The lognormal probability distribution mean parameter.
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StandardDeviation |
The lognormal probability distribution standard deviation parameter.
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LogNormalDistribution evaluates the lognormal probability density of a given set of data, xData. If parameters are not supplied, the Eval method fits the lognormal probability density function to the data by first calculating the mean and standard deviation. The lognormal probability density function is defined as:
where and are the mean and standard deviation.The DataMining package class NaiveBayesClassifier uses LognormalDistribution as a method to train continuous data.