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