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Discrete-Time Dynamic Models, by Ronald K. PEARSON, New York: Oxford University Press, 1999, ISBN 0-19-512198-8. xiii +466 pp., $85. This book emphasizes discrete-time dynamic models. The author provides an excellent [...]

Random search methods are central to "predator-prey" problems in natural phenomena where a predator is in search of a randomly located prey. Such problems aim at explaining the movement process of a variety of life forms. It is widely known that Brownian and Lévy motions optimize random search strategies and their applications have been the focus of a growing number of investigations in contemporary interdisciplinary sciences. In this review article, we discuss the applications of random search strategies that rely upon Brownian and Lévy motions and their variants. In carrying out this review, we limit our focus to the areas of foraging in ecological environments, motions of T cells and other biological organisms, and robotic searches for military and civilian targets. [ABSTRACT FROM AUTHOR]

Do Le Paul MINH. Pacific Grove, CA: Brooks/Cole Publishing, 2001, xiii + 334 pp., $90.95 (H), ISBN: 0-534-38157-X. This hook is designed as a textbook for a one-semester course for [...]

High-frequency financial log returns are known to exhibit sharp departures from the usual normality assumption. This article carries out an in-depth evaluation of the effectiveness of multidimensional non-linear mixed models that arise from considering a scale mixture-based approach to modeling non-normal log returns over a cross-sectional period of time. Simulation-based first-order and second-order comparison measures that compare the non-linear mixed model with the linear model show strong preference in favour of the non-linear mixed models. The methodology is illustrated through a thorough analysis of quarterly intra-day log returns from CISCO, DELL, COKE, and S&P500 for the years 1998-2000. [ABSTRACT FROM AUTHOR]