mirror of https://github.com/jlizier/jidt
66 lines
3.0 KiB
Java
Executable File
66 lines
3.0 KiB
Java
Executable File
/*
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* Java Information Dynamics Toolkit (JIDT)
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* Copyright (C) 2012, Joseph T. Lizier
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*
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* This program is free software: you can redistribute it and/or modify
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* it under the terms of the GNU General Public License as published by
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* the Free Software Foundation, either version 3 of the License, or
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* (at your option) any later version.
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*
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* This program is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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* GNU General Public License for more details.
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*
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* You should have received a copy of the GNU General Public License
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* along with this program. If not, see <http://www.gnu.org/licenses/>.
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*/
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package infodynamics.utils;
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/**
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* Calculators implementing this interface must provide a
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* {@link #computeSignificance()} method to compute
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* the statistical significance of their measurement, returning an analytically
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* determined distribution {@link AnalyticNullDistributionComputer}.
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*
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* @author Joseph Lizier (<a href="joseph.lizier at gmail.com">email</a>,
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* <a href="http://lizier.me/joseph/">www</a>)
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*/
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public interface AnalyticNullDistributionComputer {
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/**
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* Generate an <b>analytic</b> distribution of what a given measure would look like,
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* under a null hypothesis that the source values of our
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* samples had no relation to the destination value (possibly
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* in the context of a conditional value).
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*
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* <p>See Section II.E "Statistical significance testing" of
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* the JIDT paper below for a description of how this is done for MI,
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* conditional MI and TE as per the references below.
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* </p>
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*
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* <p><b>References:</b><br/>
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* <ul>
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* <li>J.T. Lizier, "JIDT: An information-theoretic
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* toolkit for studying the dynamics of complex systems", 2014.</li>
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* <li>Brillinger, <a href="http://www.stat.berkeley.edu/~brill/Papers/MIBJPS.pdf">
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* "Some data analyses using mutual information"</a>,
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* Brazilian Journal of Probability and Statistics, <b>18</b>, p. 163, (2004)</li>
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* <li>Cheng et al., <a href="http://www.jds-online.com/file_download/112/JDS-369.pdf">
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* "Data Information in Contingency Tables: A Fallacy of Hierarchical Loglinear Models"</a>,
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* Journal of Data Science, <b>4</b>, p. 387 (2006).</li>
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* <li>Geweke, <a href="http://dx.doi.org/10.1080/01621459.1982.10477803">
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* "Measurement of Linear Dependence and Feedback between Multiple Time Series"</a>,
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* Journal of the American Statistical Association, <b>77</b>, p. 304-313 (1982).</li>
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* <li>Barnett and Bossomaier, <a href="http://arxiv.org/abs/1205.6339">
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* "Transfer Entropy as a Log-likelihood Ratio"</a>,
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* Physical Review Letters, <b>109</b>, p. 138105+ (2012).</li>
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* </ul>
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*
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* @return the analytic distribution of channel measure scores under this null hypothesis.
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* @throws Exception
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*/
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public AnalyticMeasurementDistribution computeSignificance() throws Exception;
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}
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