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Statistical Experiments and Decisions

Statistical Experiments and Decisions
Author: Al?bert Nikolaevich Shiri?aev
Publisher: World Scientific
Total Pages: 306
Release: 2000
Genre: Mathematics
ISBN: 9789810241018

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This volume provides an exposition of some fundamental aspects of the asymptotic theory of statistical experiments. The most important of them is ?how to construct asymptotically optimal decisions if we know the structure of optimal decisions for the limit experiment?.


Statistical Experiments And Decision, Asymptotic Theory

Statistical Experiments And Decision, Asymptotic Theory
Author: Albert N Shiryaev
Publisher: World Scientific
Total Pages: 301
Release: 2000-07-04
Genre: Mathematics
ISBN: 9814494151

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This volume provides an exposition of some fundamental aspects of the asymptotic theory of statistical experiments. The most important of them is “how to construct asymptotically optimal decisions if we know the structure of optimal decisions for the limit experiment”.


Mathematical Theory of Statistics

Mathematical Theory of Statistics
Author: Helmut Strasser
Publisher: Walter de Gruyter
Total Pages: 505
Release: 2011-04-20
Genre: Mathematics
ISBN: 3110850826

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The series is devoted to the publication of monographs and high-level textbooks in mathematics, mathematical methods and their applications. Apart from covering important areas of current interest, a major aim is to make topics of an interdisciplinary nature accessible to the non-specialist. The works in this series are addressed to advanced students and researchers in mathematics and theoretical physics. In addition, it can serve as a guide for lectures and seminars on a graduate level. The series de Gruyter Studies in Mathematics was founded ca. 30 years ago by the late Professor Heinz Bauer and Professor Peter Gabriel with the aim to establish a series of monographs and textbooks of high standard, written by scholars with an international reputation presenting current fields of research in pure and applied mathematics. While the editorial board of the Studies has changed with the years, the aspirations of the Studies are unchanged. In times of rapid growth of mathematical knowledge carefully written monographs and textbooks written by experts are needed more than ever, not least to pave the way for the next generation of mathematicians. In this sense the editorial board and the publisher of the Studies are devoted to continue the Studies as a service to the mathematical community. Please submit any book proposals to Niels Jacob.


Asymptotic Methods in Statistical Decision Theory

Asymptotic Methods in Statistical Decision Theory
Author: Lucien Le Cam
Publisher: Springer Science & Business Media
Total Pages: 767
Release: 2012-12-06
Genre: Mathematics
ISBN: 1461249465

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This book grew out of lectures delivered at the University of California, Berkeley, over many years. The subject is a part of asymptotics in statistics, organized around a few central ideas. The presentation proceeds from the general to the particular since this seemed the best way to emphasize the basic concepts. The reader is expected to have been exposed to statistical thinking and methodology, as expounded for instance in the book by H. Cramer [1946] or the more recent text by P. Bickel and K. Doksum [1977]. Another pos sibility, closer to the present in spirit, is Ferguson [1967]. Otherwise the reader is expected to possess some mathematical maturity, but not really a great deal of detailed mathematical knowledge. Very few mathematical objects are used; their assumed properties are simple; the results are almost always immediate consequences of the definitions. Some objects, such as vector lattices, may not have been included in the standard background of a student of statistics. For these we have provided a summary of relevant facts in the Appendix. The basic structures in the whole affair are systems that Blackwell called "experiments" and "transitions" between them. An "experiment" is a mathe matical abstraction intended to describe the basic features of an observational process if that process is contemplated in advance of its implementation. Typically, an experiment consists of a set E> of theories about what may happen in the observational process.


Asymptotics in Statistics

Asymptotics in Statistics
Author: Lucien Le Cam
Publisher: Springer Science & Business Media
Total Pages: 299
Release: 2012-12-06
Genre: Mathematics
ISBN: 1461211662

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This is the second edition of a coherent introduction to the subject of asymptotic statistics as it has developed over the past 50 years. It differs from the first edition in that it is now more 'reader friendly' and also includes a new chapter on Gaussian and Poisson experiments, reflecting their growing role in the field. Most of the subsequent chapters have been entirely rewritten and the nonparametrics of Chapter 7 have been amplified. The volume is not intended to replace monographs on specialized subjects, but will help to place them in a coherent perspective. It thus represents a link between traditional material - such as maximum likelihood, and Wald's Theory of Statistical Decision Functions -- together with comparison and distances for experiments. Much of the material has been taught in a second year graduate course at Berkeley for 30 years.


Asymptotic Theory of Testing Statistical Hypotheses

Asymptotic Theory of Testing Statistical Hypotheses
Author: Vladimir E. Bening
Publisher: VSP
Total Pages: 312
Release: 2000-01-01
Genre: Mathematics
ISBN: 9789067643238

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The series is devoted to the publication of high-level monographs and surveys which cover the whole spectrum of probability and statistics. The books of the series are addressed to both experts and advanced students.


Statistical Decision Theory

Statistical Decision Theory
Author: F. Liese
Publisher: Springer Science & Business Media
Total Pages: 696
Release: 2008-12-30
Genre: Mathematics
ISBN: 0387731946

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For advanced graduate students, this book is a one-stop shop that presents the main ideas of decision theory in an organized, balanced, and mathematically rigorous manner, while observing statistical relevance. All of the major topics are introduced at an elementary level, then developed incrementally to higher levels. The book is self-contained as it provides full proofs, worked-out examples, and problems. The authors present a rigorous account of the concepts and a broad treatment of the major results of classical finite sample size decision theory and modern asymptotic decision theory. With its broad coverage of decision theory, this book fills the gap between standard graduate texts in mathematical statistics and advanced monographs on modern asymptotic theory.