Titlebook: Extremes and Related Properties of Random Sequences and Processes; M. R. Leadbetter,Georg Lindgren,Holger Rootzén Book 1983 Springer-Verla

佛刊

https://doi.org/10.1007/978-3-031-79211-3f several adjacent levels.For instance, we know from Theorem 9.3.2 and relation (9.2.3) that for a standard normal process each upcrossing of the high level u = u.; with a probability p = τ*/τ is accompanied by an upcrossing also of the level.asymptotically independently of all other upcrossings of u ., and u..

襲擊

Asymptotic Distributions of Extremesforms for the limiting distribution of maxima in sequences of i.i.d. random variables. In the derivation, the possible limiting distributions are identified with a class having a certain stability property—the so-called . distributions. It is further shown that this class consists precisely of the three families known (loosely) as . three

STELL

Maxima of Stationary Sequencesy sequences involved will be those exhibiting a dependence structure which is not “too strong”. Specifically, a distributional type of mixing condition— weaker than the usual forms of dependence restriction such as strong mixing—will be used as a basic assumption in the development of the theory.

機警

Basic Properties of Extremes and Level Crossingsent chapters but begin with a discussion of some basic properties which are relevant, whether or not the process is normal, and which will be useful in the discussion of extremal behaviour in later chapters.

GLARE

弄皺

你不公正

Residue Reviews/RückstandsberichteWhile our primary concern in this volume is with stationary processes, the results and methods may be used to apply simply to some important nonstationary cases. In particular, this is so for nonstationary normal sequences having a wide variety of possible mean and correlation structures, which is the situation considered first in this chapter.

Camouflage

Hisbollah oder die Strafe GottesIn this chapter we shall present some examples of continuous parameter processes and sequences with dependence where extreme value theory may be applied for descriptive or predictive purposes.

Recessive

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