Markov processes, Gaussian processes, and local times / Michael B. Marcus, Jay Rosen.

Includes bibliographical references (pages 603-610) and indexes.

Two foremost researchers present important advances in stochastic process theory by linking well understood (Gaussian) and less well understood (Markov) classes of processes. It builds to this material through 'mini-courses' on the relevant ingredients, which assume only measure-theoretic probability. This original, readable book is for researchers and advanced graduate students.

Cover; Half-title; Series-title; Title; Copyright; Dedication; Contents; 1 Introduction; 2 Brownian motion and Ray-Knight Theorems; 3 Markov processes and local times; 4 Constructing Markov processes; 5 Basic properties of Gaussian processes; 6 Continuity and boundedness of Gaussian processes; 7 Moduli of continuity for Gaussian processes; 8 Isomorphism Theorems; 9 Sample path properties of local times; 10 p-variation of Gaussian processes and local times; 11 Most visited sites of symmetric stable processes; 12 Local times of diffusions; Chapter 13 Associated Gaussian processes.

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