public class GammaDistribution extends Object implements ProbabilityDistribution, Serializable
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:
$$ f(x)= {x}^{a-1}\frac{e^{-\frac{x}{b}}} {b^a \Gamma(a)} \mbox{,}\,\,\,x \gt 0 \,\mbox{,}\,\,a \gt 0 \,\,\,\mbox{and}\,\,\, b \gt 0 \,\,\mbox{,}
$$ where a and b are the scale and shape parameters.
The DataMining package class NaiveBayesClassifier
uses GammaDistribution as a method to train continuous data.
| Constructor and Description |
|---|
GammaDistribution() |
| Modifier and Type | Method and Description |
|---|---|
double[] |
eval(double[] xData)
Fits a gamma probability distribution to
xData and
returns the probability density at each value. |
double[] |
eval(double[] xData,
Object[] parameters)
Evaluates a gamma probability distribution with a given set of
parameters at each point in
xData and returns the
probability density at each value. |
double |
eval(double xData,
Object[] parameters)
Evaluates a gamma probability density at a given point
xData. |
Object[] |
getParameters()
Returns the current parameters of the gamma probability
density function.
|
double |
getScaleParameter()
Returns the maximum-likelihood estimate found for the gamma scale
parameter.
|
double |
getShapeParameter()
Returns the maximum-likelihood estimate found for the gamma shape
parameter.
|
public double getShapeParameter()
double representing the maximum-likelihood
estimate found for the gamma shape parameterpublic double getScaleParameter()
double representing the maximum-likelihood
estimate found for the gamma scale parameterpublic double[] eval(double[] xData)
xData and
returns the probability density at each value.eval in interface DistributionxData - a double array representing the points at
which the gamma probability distribution function is to
be evaluateddouble array representing the gamma probability
density at each value of xDatapublic double[] eval(double[] xData,
Object[] parameters)
xData and returns the
probability density at each value.eval in interface ProbabilityDistributionxData - a double array representing the points at
which the gamma probability distribution function is to
be evaluatedparameters - an Object array representing the
parameters used to evaluate the gamma distribution,
see method getParametersdouble array representing the gamma probability
density at each value of xDatapublic double eval(double xData,
Object[] parameters)
xData.eval in interface ProbabilityDistributionxData - a double representing the point at which the
gamma probability distribution function is to be evaluatedparameters - an Object array representing the
parameters used to evaluate the gamma distribution,
see method getParametersdouble representing the gamma probability
density at xDatapublic Object[] getParameters()
getParameters in interface ProbabilityDistributionObject array containing the parameters
resulting from the last invocation of the
(Distribution) eval method with
the following signature, double[] eval(double[] xData).
This Object array can be used as input
to the eval methods that require an
Object array of distribution parameters
as input.Copyright © 2020 Rogue Wave Software. All rights reserved.