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Numerical Solutions for Patterns Statistics on Markov Chains
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Gregory Nuel
Published/Copyright:
October 17, 2006
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.
Keywords: exact; Gaussian approximations; large deviations; compound Poisson approximations; benchmark
Published Online: 2006-10-17
©2011 Walter de Gruyter GmbH & Co. KG, Berlin/Boston
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Keywords for this article
exact;
Gaussian approximations;
large deviations;
compound Poisson approximations;
benchmark
Articles in the same Issue
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- Low-Order Conditional Independence Graphs for Inferring Genetic Networks
- A Generalized Clustering Problem, with Application to DNA Microarrays
- A Bayes Regression Approach to Array-CGH Data
- Statistical Selection of Maintenance Genes for Normalization of Gene Expressions
- Predicting the Strongest Domain-Domain Contact in Interacting Protein Pairs
- Dimension Reduction for Classification with Gene Expression Microarray Data
- A New Type of Stochastic Dependence Revealed in Gene Expression Data
- A New Order Estimator for Fixed and Variable Length Markov Models with Applications to DNA Sequence Similarity
- Quality Optimised Analysis of General Paired Microarray Experiments
- Issues of Processing and Multiple Testing of SELDI-TOF MS Proteomic Data
- Cross-Validated Bagged Prediction of Survival
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- Combining Results of Microarray Experiments: A Rank Aggregation Approach
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