# Probabilistic models for pattern statistics

Massimiliano Goldwurm; Roberto Radicioni

RAIRO - Theoretical Informatics and Applications (2006)

- Volume: 40, Issue: 2, page 207-225
- ISSN: 0988-3754

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topGoldwurm, Massimiliano, and Radicioni, Roberto. "Probabilistic models for pattern statistics." RAIRO - Theoretical Informatics and Applications 40.2 (2006): 207-225. <http://eudml.org/doc/249702>.

@article{Goldwurm2006,

abstract = {
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.
},

author = {Goldwurm, Massimiliano, Radicioni, Roberto},

journal = {RAIRO - Theoretical Informatics and Applications},

keywords = {Pattern statistics; Markov chains; probabilistic automata; rational formal series.; pattern statistics; rational formal series},

language = {eng},

month = {7},

number = {2},

pages = {207-225},

publisher = {EDP Sciences},

title = {Probabilistic models for pattern statistics},

url = {http://eudml.org/doc/249702},

volume = {40},

year = {2006},

}

TY - JOUR

AU - Goldwurm, Massimiliano

AU - Radicioni, Roberto

TI - Probabilistic models for pattern statistics

JO - RAIRO - Theoretical Informatics and Applications

DA - 2006/7//

PB - EDP Sciences

VL - 40

IS - 2

SP - 207

EP - 225

AB -
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.

LA - eng

KW - Pattern statistics; Markov chains; probabilistic automata; rational formal series.; pattern statistics; rational formal series

UR - http://eudml.org/doc/249702

ER -

## References

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