IV . 3 . Stationary Markov Processes

  • Dy
  • Published 2008

Abstract

Recap. Last lecture, we talked about two types of Markov processes: the Poisson process and the Brownian motion process. Both of these processes are lacking another property that can be useful in analyzing stochastic processes, that of stationarity, that we defined some time ago. Stationarity and some notation. Recall from III.1: A stochastic process Y is stationary if the moments are not affected by a time shift, i.e.,

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Cite this paper

@inproceedings{Dy2008IV3, title={IV . 3 . Stationary Markov Processes}, author={Dy}, year={2008} }