Stochastic Processes

  • Tomas Cipra


Chapter 30 deals with methodology of stochastic processes (see also time series in Chap. 31): 30.1. Classification and Basic Characteristics of Stochastic Processes, 30.2. Markov Chains, 30.3. Markov Processes, 30.4. Important Stochastic Processes, 30.5. Spectral Properties of Stochastic Processes.


Discrete State Periodic Component Autocovariance Function Stationary Stochastic Process Closed Class 
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.

Further Reading

  1. Brockwell, P.J., Davis, R.A.: Time Series: Theory and Methods. Springer, New York (1987)MATHGoogle Scholar
  2. Cramer, H., Leadbetter, M.R.: Stationary and Related Stochastic Processes. Wiley, New York (1967)MATHGoogle Scholar
  3. Feller, W.: An Introduction to Probability Theory and Its Applications. Wiley, New York (1968)MATHGoogle Scholar
  4. Fuller, W.A.: Introduction to Statistical Time Series. Wiley, New York (1976)MATHGoogle Scholar
  5. Hamilton, J.D.: Time Series Analysis. Princeton University Press, Princeton, NJ (1994)MATHGoogle Scholar
  6. Leon-Garcia, A.: Probability and Random Processes. Addison-Wesley, Reading, MA (1989)MATHGoogle Scholar
  7. Malliaris, A.G., Brock, W.A.: Stochastic Methods in Economics and Finance. North-Holland, Amsterdam (1982)Google Scholar
  8. Neftci, S.N.: Mathematics of Financial Derivatives. Academic, London (2000)MATHGoogle Scholar
  9. Priestley, M.B.: Spectral Analysis and Time Series. Academic, London (1981)MATHGoogle Scholar
  10. Rektorys, K. et al.: Survey of Applicable Mathematics. Kluwer, Dordrecht (1994)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  1. 1.Dept. of Statistics, Faculty of Mathematics and PhysicsCharles University of PraguePragueCzech Republic

Personalised recommendations