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Titlebook: Approximate Distributions of Order Statistics; With Applications to R.-D. Reiss Book 1989 Springer-Verlag New York Inc. 1989 Mathematica.Pa

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期刊全称Approximate Distributions of Order Statistics
期刊简称With Applications to
影响因子2023R.-D. Reiss
视频video
学科分类Springer Series in Statistics
图书封面Titlebook: Approximate Distributions of Order Statistics; With Applications to R.-D. Reiss Book 1989 Springer-Verlag New York Inc. 1989 Mathematica.Pa
影响因子This book is designed as a unified and mathematically rigorous treatment of some recent developments of the asymptotic distribution theory of order statistics (including the extreme order statistics) that are relevant for statistical theory and its applications. Particular emphasis is placed on results concern­ ing the accuracy oflimit theorems, on higher order approximations, and other approximations in quite a general sense. Contrary to the classical limit theorems that primarily concern the weak convergence of distribution functions, our main results will be formulated in terms of the variational and the Hellinger distance. These results will form the proper springboard for the investigation of parametric approximations of nonparametric models of joint distributions of order statistics. The approxi­ mating models include normal as well as extreme value models. Several applications will show the usefulness of this approach. Other recent developments in statistics like nonparametric curve estima­ tion and the bootstrap method will be studied as far as order statistics are concerned. 1n connection with this, graphical methods will, to some extent, be explored.
Pindex Book 1989
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Approximate Distributions of Order Statistics978-1-4613-9620-8Series ISSN 0172-7397 Series E-ISSN 2197-568X
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https://doi.org/10.1007/978-3-531-19022-8 bounds correspond to those for sums of independent r.v.’s. In Section 3.1 such bounds are established in the particular case of order statistics of i.i.d. random variables with common uniform d.f. on (0,1). This section also contains two applications to moments of order statistics.
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Anforderungen an die Mitarbeiter,ributed. This result easily extends to the case of the joint distribution of a fixed number of central order statistics. In Section 4.1 we shall discuss some conditions which yield the weak and strong asymptotic normality of central order statistics.
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,Führung zur Verhaltensänderung,riety of limiting d.f.’s the situation of the present chapter turns out to be more complex than that of the preceding chapter, where weak regularity conditions guarantee the asymptotic normality of the order statistics.
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Erfolgsfaktor Performance Managementxtremes, whereas the nonparametric models contain actual distributions of sample extremes. The statistical inference within the nonparametric framework will be carried out by applying the parametric results.
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