A compound Poisson model for word occurrences in DNA sequences

We present a compound Poisson model describing the occurrence process of a set of words in a random sequence of letters. The model takes into account the frequency of the words and their overlapping structure. The model is compared with a Markov chain model in terms of fit and parsimony. Special attention is given to the detection of poor or rich regions. Several applications of the model are presented and a combination of the Markov and compound Poisson models is proposed. Copyright 2002 Royal Statistical Society.

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