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Titlebook: Statistics of Random Processes; I. General Theory Robert S. Liptser,Albert N. Shiryaev Book 2001Latest edition Springer-Verlag Berlin Heide

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Martingales and Related Processes: Continuous Time,Let (.) be a probability space and let . = (..), . ≥ 0, be a nondecreasing family of sub-σ-algebras of ..
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Square Integrable Martingales and Structure of the Functionals on a Wiener Process,Let (.) be a complete probability space, and let . = (..),. ≥ 0, be a nondecreasing (right continuous) family of sub-σ-algebras of ., each of which is augmented by sets from . having zero .-probability.
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Nonnegative Supermartingales and Martingales, and the Girsanov Theorem,Let (., ., . be a complete probability space, and let (..), ...., be a nondecreasing family of sub-σ-algebras of ., augmented by sets from . of probability zero. Let . = (.., ..) be a Wiener process and let γ = (.., ..) be a random process with
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Optimal Filtering, Interpolation and Extrapolation of Markov Processes with a Countable Number of SThe present chapter will be concerned with a pair of random processes (., .) = (.., ..), 0 ≤ . ≤ ., where the unobservable component . is a Markov process with a finite or countable number of states, and the observable process . permits the stochastic differential . where .. is a Wiener process.
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