Exact Test of Independence Using Mutual Information

Abstract

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.

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Document Details

Document Type
Technical Report
Publication Date
May 23, 2014
Accession Number
ADA618998

Entities

People

  • Daniel W. Hahs
  • Shawn D. Pethel

Organizations

  • Clarkson University

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Data Sets
  • Electronic Mail
  • Equations
  • Errors
  • Information Operations
  • Markov Processes
  • Military Research
  • Permutations
  • Probability
  • Probability Distributions
  • Random Variables
  • Rejection
  • Sampling
  • Sequences
  • Transitions

Readers

  • Regression Analysis.
  • Statistical inference.