Probabilistic models for pattern statistics
RAIRO - Theoretical Informatics and Applications - Informatique Théorique et Applications, Volume 40 (2006) no. 2, pp. 207-225.

In this work we study some probabilistic models for the random generation of words over a given alphabet used in the literature in connection with pattern statistics. Our goal is to compare models based on markovian processes (where the occurrence of a symbol in a given position only depends on a finite number of previous occurrences) and the stochastic models that can generate a word of given length from a regular language under uniform distribution. We present some results that show the differences between these two stochastic models and their relationship with the rational probabilistic measures.

DOI: 10.1051/ita:2006003
Classification: 68Q45, 68Q10, 60J99
Keywords: pattern statistics, Markov chains, probabilistic automata, rational formal series
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Goldwurm, Massimiliano; Radicioni, Roberto. Probabilistic models for pattern statistics. RAIRO - Theoretical Informatics and Applications - Informatique Théorique et Applications, Volume 40 (2006) no. 2, pp. 207-225. doi : 10.1051/ita:2006003. http://www.numdam.org/articles/10.1051/ita:2006003/

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