Numerical solutions for patterns statistics on Markov chains.
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.
Nuel
Gregory
G
Laboratoire Statistique et Genome, CNRS (8071), INRA (1152), UEVE, Evry, France. nuel@genopole.cnrs.fr
D000465:Algorithms; D001412:Bacillus subtilis / Q000235:genetics; D002874:Chromosome Mapping / Q000379:methods; D019295:Computational Biology / Q000379:methods; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D016680:Genome, Bacterial; D016679:Genome, Viral; D015497:HIV-1 / Q000235:genetics; D016013:Likelihood Functions; D008390:Markov Chains; D015233:Models, Statistical; D016011:Normal Distribution; D016012:Poisson Distribution; D011336:Probability; D015203:Reproducibility of Results; D012984:Software