We propose here a review of the methods available to compute pattern statistics on text generated by a Markov source. Theoretical, but also numerical aspects are detailed for a wide range of techniques (exact, Gaussian, large deviations, binomial and compound Poisson). The SPatt package (Statistics for Pattern, free software available at http://stat.genopole.cnrs.fr/spatt) implementing all these methods is then used to compare all these approaches in terms of computational time and reliability in the most complete pattern statistics benchmark available at the present time.
Editor-in-Chief: Stumpf, Michael P.H.
Editorial Board Member: Beaumont, Mark / Binder, Harald / Gupta, Mayetri / Hubbard, Alan E. / Husmeier, Dirk / Ji, Hongkai / Keles, Sunduz / Kerr, Kathleen / Lazzeroni, Laura / Lin, Shili / Ma, Ping / Marjoram, Paul / Mertens, Bart / Nerman, Olle / G. Petretto, Enrico / Plagnol, Vincent / Purdom, Elizabeth / Robin, Stéphane / Rzhetsky, Andrey / Sanguinetti, Guido / van der Laan, Mark J. / von Haeseler, Arndt / Weeks, Daniel E. / Wiuf, Carsten / Zhao, Hongyu
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Numerical Solutions for Patterns Statistics on Markov Chains
Gregory Nuel
1Laboratoire Statistique et Genome, CNRS (8071), INRA (1152), UEVE, Evry, France
Citation Information: Statistical Applications in Genetics and Molecular Biology. Volume 5, Issue 1, Pages –, ISSN (Online) 1544-6115, DOI: 10.2202/1544-6115.1219, October 2006
Publication History:
- Published Online:
- 2006-10-17
Keywords: exact; Gaussian approximations; large deviations; compound Poisson approximations; benchmark
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