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Titlebook: Asymptotic Nonparametric Statistical Analysis of Stationary Time Series; Daniil Ryabko Book 2019 The Author(s), under exclusive license to

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The Einstein-Podolsky-Rosen problem,o distances other than the distributional distance are considered, as well as non-stationary processes and processes more general than time series, such as multidimensional processes and processes on infinite random graphs.
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2191-5768 ractive assumption to base statistical analysis on, especially for problems for which less general qualitative assumptions, such as independence or finite memory, clearly fail. However, it has long been considered too general to be able to make statistical inference. One of the reasons for this is t
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Fundamental Theories of Physicsn algorithm for solving the so-called three-sample problem for this class of processes is presented. On the other hand, it is demonstrated that there is no asymptotically consistent test for the problem of discrimination (homogeneity testing) for stationary ergodic processes, even if one only considers binary-valued processes.
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Book 2019sumption to base statistical analysis on, especially for problems for which less general qualitative assumptions, such as independence or finite memory, clearly fail. However, it has long been considered too general to be able to make statistical inference. One of the reasons for this is that rates
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The Einstein-Podolsky-Rosen problem,topology of the distributional distance. Some examples and applications are considered. In addition, a variety of open problems concerning hypothesis testing for stationary ergodic processes is presented. Unlike the preceding chapters, here the attention is restricted to processes with a finite alphabet.
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