A Compound Poisson Model for Word Occurrences in DNA Sequences

DOI10.1111/1467-9876.00279zbMath1111.60303OpenAlexW1975525485MaRDI QIDQ3435725

Stephane Robin

Publication date: 7 May 2007

Published in: Journal of the Royal Statistical Society Series C: Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/1467-9876.00279

Mathematics Subject Classification ID

Markov chains (discrete-time Markov processes on discrete state spaces) (60J10) Applications of Markov chains and discrete-time Markov processes on general state spaces (social mobility, learning theory, industrial processes, etc.) (60J20) Point processes (e.g., Poisson, Cox, Hawkes processes) (60G55) Applications of queueing theory (congestion, allocation, storage, traffic, etc.) (60K30)

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Cites Work

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• Bounds on the distributions of extremal values of a scanning process
• Probability approximations via the Poisson clumping heuristic
• The Stein-Chen method, point processes and compensators
• A unified approach to word occurrence probabilities
• Poisson approximation for point processes via monotone couplings
• Compound Poisson approximation of word counts in DNA sequences

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