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Weak Stationarity in Stochastic Processes by Prof. Madya Dr. Umar Yusuf Madaki is a document available to read on EtoBox.

What is Weak Stationarity in Stochastic Processes about?

1. The document defines stationarity and ergodicity for stochastic processes. Stationarity simplifies the theory by imposing structures on the finite dimensional distributions. 2. Strong stationarity implies weak stationarity, though the converse is not always true. For Gaussian processes, strong and weak stationarity are equivalent. 3. The ergodic theorem states that for stationary stochastic processes, the sample mean converges almost surely or in mean square to the expected value of the process as the n

Author

Prof. Madya Dr. Umar Yusuf Madaki

Language

EN