Asymptotic Statistics

Name: Asymptotic Statistics
Brand: Birkhauser Verlag AG
SKU: 9783764322823
Price: 30.03 EUR
Availability: InStock

Autor: Rabi Bhattacharya, Manfred Denker

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Väzba: Pevná

Vydavateľ: Birkhauser Verlag AG

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These notes are based on lectures presented during the seminar on " Asymptotic Statistics" held at S...

Informácie o knihe

Autor

Rabi Bhattacharya, Manfred Denker

Jazyk

Angličtina

Väzba

Kniha - Pevná

Vydalo

1990

Stránok

122

EAN

9783764322823

ISBN

3764322829

Enbook ID

01716087

Vydavateľ

Birkhauser Verlag AG

Hmotnosť

367

Rozmery

155 x 235 x 12

Kompletný popis

These notes are based on lectures presented during the seminar on " Asymptotic Statistics" held at SchloB Reisensburg, Gunzburg, May 29-June 5, 1988. They consist of two parts, the theory of asymptotic expansions in statistics and probabilistic aspects of the asymptotic distribution theory in nonparametric statistics. Our intention is to provide a comprehensive presentation of these two subjects, leading from elementary facts to the advanced theory and recent results. Prospects for further research are also included. We would like to thank all participants for their stimulating discussions and their interest in the subjects, which made lecturing very pleasant. Special thanks are due H. Zimmer for her excellent typing. We would also like to take this opportunity to to express our thanks to the Gesellschaft fur mathematische Forschung and to the Deutsche Mathematiker Vereinigung, especially to Professor G. Fischer, for the opportunity to present these lectures and to the Birkhauser Verlag for the publication of these lecture notes. R. Bhattacharya, M. Denker Part I: Asymptotic Expansions in Statistics Rabi Bhattacharya 11 §1. CRAMER-EDGEWORTH EXPANSIONS Let Q be a probability measure on (IRk, B"), B" denoting the Borel sigmafield on IR". Assume that the s - th absolute moment of Q is finite, (1.1) P. := J II x lis Q(dx) 00, for some integer s;::: 3, and that Q is normalized, (1.2) J x(i)Q(dx) = 0 (1 ~ i ~ k), J x(i)x(j)Q(dx) = Dij (1 ~ i,j ~ k).

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