Asymptotic Theory of Testing Statistical Hypotheses PDF Download
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Author: Vladimir E. Bening
Publisher: Walter de Gruyter
ISBN: 3110935996
Category : Mathematics
Languages : en
Pages : 305
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Book Description
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.
Author: Vladimir E. Bening
Publisher: Walter de Gruyter
ISBN: 3110935996
Category : Mathematics
Languages : en
Pages : 305
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Book Description
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.
Author: Vladimir E. Bening
Publisher:
ISBN: 9783110622775
Category :
Languages : en
Pages :
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Book Description
Author: Odile Pons
Publisher: World Scientific
ISBN: 9814531766
Category : Mathematics
Languages : en
Pages : 304
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Book Description
An overview of the asymptotic theory of optimal nonparametric tests is presented in this book. It covers a wide range of topics: Neyman–Pearson and LeCam's theories of optimal tests, the theories of empirical processes and kernel estimators with extensions of their applications to the asymptotic behavior of tests for distribution functions, densities and curves of the nonparametric models defining the distributions of point processes and diffusions. With many new test statistics developed for smooth curves, the reliance on kernel estimators with bias corrections and the weak convergence of the estimators are useful to prove the asymptotic properties of the tests, extending the coverage to semiparametric models. They include tests built from continuously observed processes and observations with cumulative intervals. Contents:IntroductionAsymptotic TheoryNonparametric Tests for One SampleTwo-Sample TestsMulti-Dimensional TestsNonparametric Tests for ProcessesNonparametric Tests Under Censoring or TruncationSequential Tests Readership: Researchers and graduates in the field of probability and statistics, and biomathematics. Keywords:Nonparametric Tests;Weak Convergence;Empirical Process;Kernel Estimator;Density;Nonparametric Regression;Point Process;Diffusion;Homogeneity;Symmetry;Goodness-of-Fit;MonotonyKey Features:The book gives a survey of the theory and explains how to build optimal tests in statisticsThe asymptotic efficiency and the asymptotic equivalence of tests are carefully illustrated in the examples and exercises along with their correctionsReviews: “This is a very nice book which will soon become one of the basic references in the field of statistical testing of hypotheses in nonparametric statistics. The author collected a lot of key results spread out in the rather vast literature and described them in a uniform manner.” Zentralblatt MATH
Author: Ning-Zhong Shi
Publisher: World Scientific
ISBN: 9812814361
Category : Science
Languages : en
Pages : 320
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Book Description
This book presents up-to-date theory and methods of statistical hypothesis testing based on measure theory. The so-called statistical space is a measurable space adding a family of probability measures. Most topics in the book will be developed based on this term. The book includes some typical data sets, such as the relation between race and the death penalty verdict, the behavior of food intake of two kinds of Zucker rats, and the per capita income and expenditure in China during the 1978?2002 period. Emphasis is given to the process of finding appropriate statistical techniques and methods of evaluating these techniques.
Author: E.L. Lehmann
Publisher: Springer Nature
ISBN: 3030705781
Category : Mathematics
Languages : en
Pages : 1016
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Book Description
The third edition of Testing Statistical Hypotheses updates and expands upon the classic graduate text, emphasizing optimality theory for hypothesis testing and confidence sets. The principal additions include a rigorous treatment of large sample optimality, together with the requisite tools. In addition, an introduction to the theory of resampling methods such as the bootstrap is developed. The sections on multiple testing and goodness of fit testing are expanded. The text is suitable for Ph.D. students in statistics and includes over 300 new problems out of a total of more than 760.
Author: Erich L. Lehmann
Publisher: Springer Science & Business Media
ISBN: 038727605X
Category : Mathematics
Languages : en
Pages : 795
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Book Description
The third edition of Testing Statistical Hypotheses updates and expands upon the classic graduate text, emphasizing optimality theory for hypothesis testing and confidence sets. The principal additions include a rigorous treatment of large sample optimality, together with the requisite tools. In addition, an introduction to the theory of resampling methods such as the bootstrap is developed. The sections on multiple testing and goodness of fit testing are expanded. The text is suitable for Ph.D. students in statistics and includes over 300 new problems out of a total of more than 760.
Author: Erich Leo Lehmann
Publisher: John Wiley & Sons
ISBN:
Category : Mathematics
Languages : en
Pages : 632
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Book Description
This book covers the theory of hypotheses testing and of estimation by confidence intervals. Accompanying Theory of Point Estimation (1983) to cover the main topics of classical statistics, including theory and its principal applications, this second edition contains more on confidence intervals, simultaneous inference, admissibility, and conditioning. The book is thoroughly updated throughout with a new section on conditional inference and an expansion of multivariate material.
Author: Masahito Hayashi
Publisher: World Scientific
ISBN: 981448198X
Category : Science
Languages : en
Pages : 560
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Book Description
' Quantum statistical inference, a research field with deep roots in the foundations of both quantum physics and mathematical statistics, has made remarkable progress since 1990. In particular, its asymptotic theory has been developed during this period. However, there has hitherto been no book covering this remarkable progress after 1990; the famous textbooks by Holevo and Helstrom deal only with research results in the earlier stage (1960s-1970s). This book presents the important and recent results of quantum statistical inference. It focuses on the asymptotic theory, which is one of the central issues of mathematical statistics and had not been investigated in quantum statistical inference until the early 1980s. It contains outstanding papers after Holevo's textbook, some of which are of great importance but are not available now. The reader is expected to have only elementary mathematical knowledge, and therefore much of the content will be accessible to graduate students as well as research workers in related fields. Introductions to quantum statistical inference have been specially written for the book. Asymptotic Theory of Quantum Statistical Inference: Selected Papers will give the reader a new insight into physics and statistical inference. Contents:Hypothesis TestingQuantum Cramér-Rao Bound in Mixed States ModelQuantum Cramér-Rao Bound in Pure States ModelGroup Symmetric Approach to Pure States ModelLarge Deviation Theory in Quantum EstimationFuther Topics on Quantum Statistical Inference Readership: Graduate students in quantum physics, mathematical physics, and probability and statistics. Keywords:Quantum Information;Estimation Theory;Statistics;Statistical Inference;Mathematical Physics;Asymptotic Theory;Hypothesis TestingReviews:“This book will give the scholars new insight into physics and statistical inference.”Zentralblatt MATH '
Author: Indra Mohan Chakravarti
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
Author: W. Jackson Hall
Publisher: CRC Press
ISBN: 1498726089
Category : Mathematics
Languages : en
Pages : 321
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Book Description
Provides accessible introduction to large sample theory with moving alternatives Elucidates mathematical concepts using simple practical examples Includes problem sets and solutions for each chapter Uses the moving alternative formulation developed by LeCam but requires a minimum of mathematical prerequisites
