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Introduction

  • V. G. KulkarniEmail author
Chapter
Part of the Springer Texts in Statistics book series (STS)

Abstract

A stochastic process is a probability model that describes the evolution of a system evolving randomly in time. If we observe the system at a set of discrete times, say at the end of every day or every hour, we get a discrete-time stochastic process. On the other hand, if we observe the system continuously at all times, we get a continuous-time stochastic process. We begin with examples of the discrete- and continuous-time stochastic processes.

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Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.Department of Statistics and Operations ResearchUniversity of North CarolinaChapel HillUSA

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