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Stochastic Processes

Chapter
Part of the Springer Texts in Statistics book series (STS, volume 0)

Abstract

A stochastic process may be understood as a continuous-time series or as an extension of the time series that includes both discrete-time and continuous-time series. In this chapter we discuss a few well-known stochastic processes, which in a certain sense define the term stochastic processes. These include both discrete-time and continuous-time processes that have not been previously discussed in details. Again, our focus is the limiting behaviors of these processes.

Keywords

Markov Chain Brownian Motion Poisson Process GARCH Model Interarrival Time 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  1. 1.Department of StatisticsUniversity of CaliforniaDavisUSA

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