by C. Radhakrishna Rao, D.N. Shanbhag (1994)
The ICFE was originally introduced to characterize a probability distribution by some invariant property under a stochastic change (damage) to the original random variable, and it is a generalization of a certain version of the Choquet-Deny convolution equation which occurs in potential theory. The solution of the ICFE is obtained using certain properties of exchangeable random elements or martingales, amongst other things. The solutions to these functional equations provide a unified and elegant approach to characterizations of the exponential, geometric, Pareto, Weibull, stable, Poisson and other distributions under a variety of stochastic properties of the random variable. The ICFE also plays an important role in renewal processes, potential theory and other applications of stochastic processes. Several illustrative examples are given to show the wide applicability of the ICFE. Besides the general theory associated with the ICFE and related equations, the book introduces new probability tools and techniques which should be of interest to research workers in probability and statistics, as well as those working in other areas such as biology, medicine and engineering.
V.I Klyatskin
Divided into five parts, part I of this book gives mathematical formulation for the physical models of transport, diffusion, propagation. Parts II and III set up and apply the techniques of variational calculus and stochastic analysis. Part IV takes up issues for the coherent phenomena in stochastic dynamical systems. Part V contains appendixes.
Lars Gårding, Torbjörn Tambour
The aim of this book is to teach the reader the topics in algebra which are useful in the study of computer science. In a clear, concise style, the author present the basic algebraic structures, and their applications to such topics as the finite Fourier transform, coding, complexity, and automata theory. The book can also be read profitably as a course in applied algebra for mathematics students.
Jean-Yves Girard, Yves Lafont, Laurent Regnier
Linear logic, introduced in 1986 by J.-Y. Girard, is based upon a fine grain analysis of the main proof-theoretical notions of logic. The subject develops along the lines of denotational semantics, proof nets and the geometry of interaction. Its basic dynamical nature has attracted computer scientists, and various promising connections have been made in the areas of optimal program execution, interaction nets and knowledge representation. This book is the refereed proceedings of the first international meeting on linear logic held at Cornell University, in June 1993. Survey papers devoted to specific areas of linear logic, as well as an extensive general introduction to the subject by J.-Y. Girard, have been added, so as to make this book a valuable tool both for the beginner and for the advanced researcher.
Joseph M. Hilbe
"This second edition of Hilbe's Negative Binomial Regression is a substantial enhancement to the popular first edition. The only text devoted entirely to the negative binomial model and its many variations, nearly every model discussed in the literature is addressed. The theoretical and distributional background of each model is discussed, together with examples of their construction, application, interpretation, and evaluation. Complete Stata and R code are provided throughout the text, with additional code (plus SAS), derivations, and data provided on the book's website. Written for the practicing researcher, the text begins with an examination of risk and rate ratios, and of the estimating algorithms used to model count data. The book then gives an in-depth analysis of Poisson regression and an evaluation of the meaning and nature of overdispersion, followed by a comprehensive analysis of the negative binomial distribution and of its parameterizations into various models for evaluating count data"--