Stochastic Processes: Holden-Day Series in Probability and Statistics - Hardcover

Stochastic Processes: Holden-Day Series In Probability And Statistics is a comprehensive textbook written by Emanuel Parzen. The book provides an in-depth study of stochastic processes, which are mathematical models used to describe random phenomena that evolve over time. The book covers a wide range of topics, including Markov processes, Poisson processes, Brownian motion, and martingales. It also includes discussions on the applications of stochastic processes in various fields, such as finance, engineering, and physics.The book is divided into four parts, each focusing on different aspects of stochastic processes. Part I introduces the basic concepts of stochastic processes, such as probability spaces, random variables, and conditional expectations. Part II covers discrete-time Markov processes, including their properties, classification, and applications. Part III discusses continuous-time Markov processes, including Poisson processes, birth-death processes, and diffusion processes. Part IV covers martingales, which are stochastic processes that have a property of being fair games.The book is written in a clear and concise manner, with numerous examples and exercises to help readers understand the concepts. It is suitable for graduate students and researchers in mathematics, statistics, and related fields who want to deepen their understanding of stochastic processes. Overall, Stochastic Processes: Holden-Day Series In Probability And Statistics is an essential reference for anyone interested in the theory and applications of stochastic processes.This scarce antiquarian book is a facsimile reprint of the old original and may contain some imperfections such as library marks and notations. Because we believe this work is culturally important, we have made it available as part of our commitment for protecting, preserving, and promoting the world's literature in affordable, high quality, modern editions, that are true to their original work.