(Paperback)

(Hardback)

The modeling of stochastic dependence is fundamental for understanding random systems evolving in time. With an historical overview, this book describes the state of knowledge about selfsimilar processes and their applications. It emphasizes concepts, definitions and basic properties, giving the reader a road map of the realm of selfsimilarity.

(Paperback)

Revised and updated edition of the classic of advanced statistics. Uses concepts of gambling to develop important ideas in probability theory. "Strongly recommended." - Journal of the American Statistical Association. 2014 edition.

(Paperback)

Well-written and accessible, this classic introductory treatment offers examples of the wide variety of empirical phenomena for which stochastic processes provide mathematical models and develops the methods of probability model-building. 1962 edition.