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ISBN: 0387900853 3540900853 1461298547 1461298520 9780387900858 9783540900856 Year: 1974 Volume: 17 Publisher: New York, N.Y. Springer
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ISBN: 0415272327 9781482288100 1482288109 9780415272322 Year: 2002 Publisher: London Taylor & Francis
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ISBN: 3540178740 0387178740 3642727190 3642727174 Year: 1987 Publisher: Berlin Springer
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ISBN: 0198535937 9780198535935 Year: 1992 Volume: 1 Publisher: Oxford Clarendon
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This book presents a unified treatment of the prediction process approach to continuous time stochastic processes. The underling idea is that there are two kinds of time: stationary physical time and the moving observer's time. By developing this theme, the author develops a theory of stochastic processes whereby two processes are considered which coexist on the same probability space. In this way, the observer' process is strongly Markovian. Consequently, any measurable stochastic process of a real parameter may be regarded as a homogeneous strong Markov process in an appropriate setting. This leads to a unifying principle for the representation of general processes in terms of martingales which facilitates the prediction of their properties. While the ideas are advanced, the methods are reasonable elementary and should be accessible to readers with basic knowledge of measure theory, functional analysis, stochastic integration, and probability on the level of the convergence theorem for positive super-martingales.
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ISBN: 081623034X 9780816230341 Year: 1972 Publisher: San Francisco Holden-Day
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ISBN: 0126848807 0126848823 1322560285 1483269272 Year: 1974 Publisher: Orlando Institute of internal auditors
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ISBN: 0201116901 9780201116908 Year: 1984 Publisher: Reading (Mass.) : Addison-Wesley,
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ISBN: 0412984318 Year: 1994 Publisher: New York, N.Y. Chapman & Hall
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ISBN: 0387402640 9780387402642 1441923195 9786611114329 1281114324 0387289828 Year: 2005 Publisher: New York (N.Y.) : Springer-Verlag,
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ISBN: 0081023634 1785482459 9780081023631 9781785482458 Year: 2018 Publisher: London : Oxford : ISTE Press ; Elsevier,
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