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Titlebook: Heavy-Tailed Time Series; Rafal Kulik,Philippe Soulier Textbook 2020 Springer Science+Business Media, LLC, part of Springer Nature 2020 Ex

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Rafał Kulik,Philippe Soulierinsulfat auf Verhaltensstörungen aggressiver und hyperkinetischer Art bei Kindern und bei aggressiven Psychopathen betreffen. Sie betonen auch die großen Dosen, die hierbei gegeben und auch von den Patienten vertragen werden können.
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Regular variation of series and random sumssult of the chapter, Theorem .. We will apply it to series with deterministic weights and random sums. The results of this chapter will be useful to study certain models in Part III. Throughout this chapter, . denotes an arbitrary norm on . and . the associated matrix norm.
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Estimation for extremally independent time serieshe boundedness . on . which consists of sets separated from . and that we say that a Borel measure . on . is .-boundedly finite if and only if . for all .. Recall also that a sequence of .-boundedly finite measures . converges .-vaguely. to . if . for all .-continuity sets ..
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Rafał Kulik,Philippe SoulierDie Wirkungen und der klinische Gebrauch der Amphetamine haben in mancherlei Hinsicht pharmakologisches Interesse erweckt. In den 20 Jahren, in denen diese Mittel in klinischer Prüfung standen, sind viele Anwendungsmöglichkeiten vorgeschlagen worden. In diesem Kapitel sollen folgende Punkte kurz behandelt werden :
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Dealing with extremal independenceConsider a regularly varying random vector . which is extremally independent.
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Regularly varying time seriesThis chapter introduces the central object of this book: we consider regularly varying time series, that is, sequences of .-dimensional random vectors indexed by ., whose finite-dimensional distributions are all regularly varying.
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Convergence to stable and extremal processesIn this chapter, we consider a real-valued stationary time series .. We will apply the point process convergence results of Chapter 7 to obtain weak convergence of partial maxima and partial sum processes, the latter when the tail index ..
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