The Probability Theory of Patterns and Runs has had a long and distinguished history, starting with the work of de Moivre in the 18th century and that of von Mises in the early 1920's, and continuing with the renewal-theoretic results in Feller's classic text An Introduction to Probability Theory and its Applications, Volume 1. It is worthwhile to note, in particular, that de Moivre, in the third edition of The Doctrine of Chances (1756, reprinted by Chelsea in 1967, pp. 254-259), provides the generating function for the waiting time for the appearance of k consecutive successes. During the 1940's, statisticians such as Mood, Wolfowitz, David and Mosteller studied the distribution theory, both exact and asymptotic, of run-related statistics, thereby laying the foundation for several exact run tests. In the last two decades or so, the theory has seen an impressive re-emergence, primarily due to important developments in Molecular Biology, but also due to related research thrusts in Reliability Theory, Distribution Theory, Combinatorics, and Statistics.
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The probabilistic analysis of patterns and runs plays a critical role in fields as diverse as reliability, molecular biology, distribution theory and statistics. The papers in this volume have been written by a collection of research workers who are experts in these (and other) fields. The probabilistic methods they employ include the Stein-Chen technique of Poisson approximation, "generating functionology", Markov chain techniques, the "independence principle", combinatorial probability, exchangeability, and hypergeometric evaluations. The volume has been divided into three sections, entitled combinatorial probability and distribution theory, reliability, and limit theorems and approximations. It should be of interest to graduate students and research workers in applied probability, reliability theory, combinatorics and statistics. Most of the papers in the volume are expository in nature and can be used as an introduction to a dynamic and growing area of research.
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