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package de.lmu.ifi.dbs.elki.math.statistics.distribution.estimator;
/*
This file is part of ELKI:
Environment for Developing KDD-Applications Supported by Index-Structures
Copyright (C) 2015
Ludwig-Maximilians-Universität München
Lehr- und Forschungseinheit für Datenbanksysteme
ELKI Development Team
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU Affero General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU Affero General Public License for more details.
You should have received a copy of the GNU Affero General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
import de.lmu.ifi.dbs.elki.math.statistics.distribution.ExponentialDistribution;
import de.lmu.ifi.dbs.elki.utilities.documentation.Reference;
import de.lmu.ifi.dbs.elki.utilities.optionhandling.AbstractParameterizer;
/**
* Estimate the parameters of a Gamma Distribution, using the methods of
* L-Moments (LMM).
*
* Reference:
* <p>
* J. R. M. Hosking<br />
* Fortran routines for use with the method of L-moments Version 3.03<br />
* IBM Research.
* </p>
*
*
* @author Erich Schubert
*
* @apiviz.has ExponentialDistribution
*/
@Reference(authors = "J.R.M. Hosking", title = "Fortran routines for use with the method of L-moments Version 3.03", booktitle = "IBM Research Technical Report")
public class ExponentialLMMEstimator extends AbstractLMMEstimator<ExponentialDistribution> {
/**
* Static instance.
*/
public static final ExponentialLMMEstimator STATIC = new ExponentialLMMEstimator();
/**
* Constructor. Private: use static instance.
*/
private ExponentialLMMEstimator() {
super();
}
@Override
public int getNumMoments() {
return 2;
}
@Override
public ExponentialDistribution estimateFromLMoments(double[] xmom) {
double scale = 2. * xmom[1];
if (!(scale > 0.)) {
throw new ArithmeticException("Data with non-positive scale cannot be exponential distributed.");
}
return new ExponentialDistribution(1. / scale, xmom[0] - scale);
}
@Override
public Class<? super ExponentialDistribution> getDistributionClass() {
return ExponentialDistribution.class;
}
/**
* Parameterization class.
*
* @author Erich Schubert
*
* @apiviz.exclude
*/
public static class Parameterizer extends AbstractParameterizer {
@Override
protected ExponentialLMMEstimator makeInstance() {
return STATIC;
}
}
}
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