Exercises in Probability

Derived from extensive teaching experience in Paris, this second edition now includes over 100 exercises in probability. New exercises have been added to reflect important areas of current research in probability theory, including infinite divisibility of stochastic processes, past-future martingales and fluctuation theory. For each exercise the authors provide detailed solutions as well as references for preliminary and further reading. There are also many insightful notes to motivate the student and set the exercises in context. Students will find these exercises extremely useful for easing the transition between simple and complex probabilistic frameworks. Indeed, many of the exercises here will lead the student on to frontier research topics in probability. Along the way, attention is drawn to a number of traps into which students of probability often fall. This book is ideal for independent study or as the companion to a course in advanced probability theory. 'In conclusion, this is an excellent book, which should be in every library, and also on the bookshelf of anyone with interests in advanced probability and random processes.' Society for Industrial and Applied Mathematics '... extremely useful for graduate and postgraduate students and those who want to better understand advanced probability theory.' European Mathematical Society Newsletter '... although the book could profitably be used as a companion to a graduate course in probability theory, it is probably best designed for the doctoral student who can read it alongside the source material. Used in that way, the book is a magnificent resource ... consistency and clarity of mathematical style ... For beginning researchers in stochastic mathematics, this book comes highly recommended and libraries should obtain a copy.' Journal of the Royal Statistical Society: Series A 'This book, written in an inspiring style, can be used together with almost any advanced course and strongly recommend to doctoral and master students in the area of probability and stochastic processes. Young researchers and university teachers as well as professionals can benefit a lot from this book.' Jordan M. Stoyanov, Zentralblatt MATHPreface to the Second Edition; Preface to the First Edition; 1. Measure theory and probability; 2. Independence and conditioning; 3. Gaussian variables; 4. Distributional computations; 5. Convergence of random variables; 6. Random processes; Where is the notion N discussed?; Final suggestions: how to go further?; References; Index.