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Article

Exact Test of Independence Using Mutual Information

1
Army RDECOM, RDMR-WDS-WO, Redstone Arsenal, AL 35898, USA
2
Torch Technologies, Inc., Huntsville, AL 35802, USA
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Author to whom correspondence should be addressed.
Entropy 2014, 16(5), 2839-2849; https://doi.org/10.3390/e16052839
Received: 18 February 2014 / Revised: 15 May 2014 / Accepted: 20 May 2014 / Published: 23 May 2014
(This article belongs to the Special Issue Information in Dynamical Systems and Complex Systems)
Using a recently discovered method for producing random symbol sequences with prescribed transition counts, we present an exact null hypothesis significance test (NHST) for mutual information between two random variables, the null hypothesis being that the mutual information is zero (i.e., independence). The exact tests reported in the literature assume that data samples for each variable are sequentially independent and identically distributed (iid). In general, time series data have dependencies (Markov structure) that violate this condition. The algorithm given in this paper is the first exact significance test of mutual information that takes into account the Markov structure. When the Markov order is not known or indefinite, an exact test is used to determine an effective Markov order. View Full-Text
Keywords: mutual information; significance test; surrogate data mutual information; significance test; surrogate data
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MDPI and ACS Style

Pethel, S.D.; Hahs, D.W. Exact Test of Independence Using Mutual Information. Entropy 2014, 16, 2839-2849. https://doi.org/10.3390/e16052839

AMA Style

Pethel SD, Hahs DW. Exact Test of Independence Using Mutual Information. Entropy. 2014; 16(5):2839-2849. https://doi.org/10.3390/e16052839

Chicago/Turabian Style

Pethel, Shawn D., and Daniel W. Hahs 2014. "Exact Test of Independence Using Mutual Information" Entropy 16, no. 5: 2839-2849. https://doi.org/10.3390/e16052839

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