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java.lang.Objectjphase.fit.ContPhaseFitter
jphase.fit.MLContPhaseFitter
jphase.fit.EMHyperErlangFit
public class EMHyperErlangFit
This class implements the Maximum Likelihood method proposed by Thümmler, Buchholz and Telek in "A novel approach for fitting probability distributions to real trace data with the EM algorithm", 2005. The method matches the likelilihood of any distribution to a subclass of Phase-Type distributions known as Hyper-Erlang distributions.
Field Summary | |
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static double |
precision
Precision for the convergence criterion in the algorithm |
static double |
precisionCV
Precision for the convergence criterion in the coefficient of variance |
Fields inherited from class jphase.fit.ContPhaseFitter |
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data, var |
Constructor Summary | |
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EMHyperErlangFit(double[] data)
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Method Summary | |
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HyperErlangVar |
doFitHyperErlang(double[] data)
Returns a HyperErlang variable with the best fit |
double |
doFitNM(double[] data,
HyperErlangVar var)
This method returns a completely specified HyperErlang variable, such that it has the best likelihood between all the possible combinations of N phases in M branches |
double |
doFitNMR(double[] data,
HyperErlangVar var)
This method returns a completely specified HyperErlang variable, such that it has the best likelihood after the execution of the EM algorithm for the case where the variable has N phases in M branches, distributed as determined by the vector r |
DenseContPhaseVar |
fit()
Returns a HyperErlang variable with the best fit, in the form of a Dense Continuous Phase variable |
Methods inherited from class jphase.fit.MLContPhaseFitter |
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getLogLikelihood |
Methods inherited from class java.lang.Object |
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clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Field Detail |
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public static double precision
public static double precisionCV
Constructor Detail |
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public EMHyperErlangFit(double[] data)
data
- Method Detail |
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public DenseContPhaseVar fit()
fit
in interface PhaseFitter
fit
in class ContPhaseFitter
PhaseFitter.fit()
public HyperErlangVar doFitHyperErlang(double[] data)
data
- non-negative data trace from independent
experiments to be fitted
public double doFitNM(double[] data, HyperErlangVar var)
data
- non-negative data trace from independent
experiments to be fittedvar
- HyperErlang variable with the parameters
N and M determined
public double doFitNMR(double[] data, HyperErlangVar var)
data
- non-negative data trace from independent
experiments to be fittedvar
- HyperErlang variable with the parameters
N, M and r determined
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