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Asymptotic Theory Of Testing Statistical Hypotheses
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Book Synopsis Asymptotic Theory of Testing Statistical Hypotheses by : Vladimir E. Bening
Download or read book Asymptotic Theory of Testing Statistical Hypotheses written by Vladimir E. Bening and published by Walter de Gruyter. This book was released on 2011-08-30 with total page 305 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Asymptotic Theory of Testing Statistical Hypotheses: Efficient Statistics, Optimality, Power Loss, and Deficiency (Modern Probability and Statistics) by : Vladimir E. Bening
Download or read book Asymptotic Theory of Testing Statistical Hypotheses: Efficient Statistics, Optimality, Power Loss, and Deficiency (Modern Probability and Statistics) written by Vladimir E. Bening and published by . This book was released on with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Testing Statistical Hypotheses by : Erich Leo Lehmann
Download or read book Testing Statistical Hypotheses written by Erich Leo Lehmann and published by Springer Verlag. This book was released on 1986 with total page 600 pages. Available in PDF, EPUB and Kindle. Book excerpt: This classic work, now available from Springer, summarizes developments in the field of hypotheses testing. Optimality considerations continue to provide the organizing principle; however, they are now tempered by a much stronger emphasis on the robustness properties of the resulting procedures. This book is an essential reference for any graduate student in statistics.
Book Synopsis Testing Statistical Hypotheses by : E.L. Lehmann
Download or read book Testing Statistical Hypotheses written by E.L. Lehmann and published by Springer Nature. This book was released on 2022-06-22 with total page 1016 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Statistical Hypothesis Testing by : Ning-Zhong Shi
Download or read book Statistical Hypothesis Testing written by Ning-Zhong Shi and published by World Scientific. This book was released on 2008 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Testing Statistical Hypotheses by : Erich L. Lehmann
Download or read book Testing Statistical Hypotheses written by Erich L. Lehmann and published by Springer Science & Business Media. This book was released on 2006-03-30 with total page 795 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Asymptotic Theory of Quantum Statistical Inference by : Masahito Hayashi
Download or read book Asymptotic Theory of Quantum Statistical Inference written by Masahito Hayashi and published by World Scientific. This book was released on 2005-02-21 with total page 560 pages. Available in PDF, EPUB and Kindle. Book excerpt: ' 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 '
Book Synopsis Testing Statistical Hypotheses by : Erich Leo Lehmann
Download or read book Testing Statistical Hypotheses written by Erich Leo Lehmann and published by John Wiley & Sons. This book was released on 1986 with total page 632 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Asymptotic Theory of Statistical Tests and Estimation by : Indra Mohan Chakravarti
Download or read book Asymptotic Theory of Statistical Tests and Estimation written by Indra Mohan Chakravarti and published by . This book was released on 1980 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt: Some memorable incidentes in probabilistic/statistica studies; Large deviation, tests, and estimates; Applications of characteristic function in solving some distribution problems; A chernoff-savage theorem for correlation ranl statistics with applications to sequential testing; Wiener - levy models, spherically exchangeable time series, and simultaneous inference in growth curve analysis; A note to the chung - erdors - sirao theorem; Asymptotic separation of distribution and convergence properties of tests and estimators; Density estimation: are theoretical results useful in practice? Stability theorems for characterizations of the normal and of the degenerate distribution; Estimation of the support contour-line of a probability law: limit law; Some estimation problems for the compound poisson distribution; A decomposition of infinite order and extreme multivariate distributions; Correction terms for multinomial large deviations; On a theorem of hoeffding; Sequential minimum probability ratio tests.
Book Synopsis A Course in the Large Sample Theory of Statistical Inference by : W. Jackson Hall
Download or read book A Course in the Large Sample Theory of Statistical Inference written by W. Jackson Hall and published by CRC Press. This book was released on 2023-12-14 with total page 321 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Book Synopsis Elements of Large-Sample Theory by : E.L. Lehmann
Download or read book Elements of Large-Sample Theory written by E.L. Lehmann and published by Springer Science & Business Media. This book was released on 2006-04-18 with total page 640 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written by one of the main figures in twentieth century statistics, this book provides a unified treatment of first-order large-sample theory. It discusses a broad range of applications including introductions to density estimation, the bootstrap, and the asymptotics of survey methodology. The book is written at an elementary level making it accessible to most readers.
Book Synopsis Statistical Tests of Nonparametric Hypotheses by : Odile Pons
Download or read book Statistical Tests of Nonparametric Hypotheses written by Odile Pons and published by World Scientific. This book was released on 2013-10-04 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Book Synopsis Asymptotic Statistics by : A. W. van der Vaart
Download or read book Asymptotic Statistics written by A. W. van der Vaart and published by Cambridge University Press. This book was released on 2000-06-19 with total page 470 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is an introduction to the field of asymptotic statistics. The treatment is both practical and mathematically rigorous. In addition to most of the standard topics of an asymptotics course, including likelihood inference, M-estimation, the theory of asymptotic efficiency, U-statistics, and rank procedures, the book also presents recent research topics such as semiparametric models, the bootstrap, and empirical processes and their applications. The topics are organized from the central idea of approximation by limit experiments, which gives the book one of its unifying themes. This entails mainly the local approximation of the classical i.i.d. set up with smooth parameters by location experiments involving a single, normally distributed observation. Thus, even the standard subjects of asymptotic statistics are presented in a novel way. Suitable as a graduate or Master s level statistics text, this book will also give researchers an overview of the latest research in asymptotic statistics.
Book Synopsis Statistical Inference: Testing Of Hypotheses by : Srivastava & Srivastava
Download or read book Statistical Inference: Testing Of Hypotheses written by Srivastava & Srivastava and published by PHI Learning Pvt. Ltd.. This book was released on 2009-12 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: it emphasizes on J. Neyman and Egon Pearson's mathematical foundations of hypothesis testing, which is one of the finest methodologies of reaching conclusions on population parameter. Following Wald and Ferguson's approach, the book presents Neyman-Pearson theory under broader premises of decision theory resulting into simplification and generalization of results. On account of smooth mathematical development of this theory, the book outlines the main result on Lebesgue theory in abstract spaces prior to rigorous theoretical developments on most powerful (MP), uniformly most powerful (UMP) and UMP unbiased tests for different types of testing problems. Likelihood ratio tests their large sample properties to variety of testing situations and connection between confidence estimation and testing of hypothesis have been discussed in separate chapters. The book illustrates simplification of testing problems and reduction in dimensionality of class of tests resulting into existence of an optimal test through the principle of sufficiency and invariance. It concludes with rigorous theoretical developments on non-parametric tests including their optimality, asymptotic relative efficiency, consistency, and asymptotic null distribution.
Book Synopsis Inference and Asymptotics by : D.R. Cox
Download or read book Inference and Asymptotics written by D.R. Cox and published by CRC Press. This book was released on 1994-03-01 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: Likelihood and its many associated concepts are of central importance in statistical theory and applications. The theory of likelihood and of likelihood-like objects (pseudo-likelihoods) has undergone extensive and important developments over the past 10 to 15 years, in particular as regards higher order asymptotics. This book provides an account of this field, which is still vigorously expanding. Conditioning and ancillarity underlie the p*-formula, a key formula for the conditional density of the maximum likelihood estimator, given an ancillary statistic. Various types of pseudo-likelihood are discussed, including profile and partial likelihoods. Special emphasis is given to modified profile likelihood and modified directed likelihood, and their intimate connection with the p*-formula. Among the other concepts and tools employed are sufficiency, parameter orthogonality, invariance, stochastic expansions and saddlepoint approximations. Brief reviews are given of the most important properties of exponential and transformation models and these types of model are used as test-beds for the general asymptotic theory. A final chapter briefly discusses a number of more general issues, including prediction and randomization theory. The emphasis is on ideas and methods, and detailed mathematical developments are largely omitted. There are numerous notes and exercises, many indicating substantial further results.
Book Synopsis Testing Statistical Hypotheses of Equivalence and Noninferiority by : Stefan Wellek
Download or read book Testing Statistical Hypotheses of Equivalence and Noninferiority written by Stefan Wellek and published by CRC Press. This book was released on 2010-06-24 with total page 431 pages. Available in PDF, EPUB and Kindle. Book excerpt: While continuing to focus on methods of testing for two-sided equivalence, Testing Statistical Hypotheses of Equivalence and Noninferiority, Second Edition gives much more attention to noninferiority testing. It covers a spectrum of equivalence testing problems of both types, ranging from a one-sample problem with normally distributed observations
Book Synopsis A Course in the Large Sample Theory of Statistical Inference by : William Jackson Hall
Download or read book A Course in the Large Sample Theory of Statistical Inference written by William Jackson Hall and published by . This book was released on 2023-12 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book provides an accessible but rigorous introduction to asymptotic theory in parametric statistical models. Asymptotic results for estimation and testing are derived using the "moving alternative" formulation due to R. A. Fisher and L. Le Cam. Later chapters include discussions of linear rank statistics and of chi-squared tests for contingency table analysis, including situations where parameters are estimated from the complete ungrouped data. The book is based on lecture notes prepared by the first author, subsequently edited, expanded and updated by the second author. Some facility with linear algebra and with real analysis including "epsilon-delta" arguments is required. Concepts and results from measure theory are explained when used. Familiarity with undergraduate probability and statistics including basic concepts of estimation and hypothesis testing is necessary, and experience with applying these concepts to data analysis would be very helpful"--
