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Higher Order Asymptotic Optimality In Testing Problems With Nuisance Parameters
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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 Statistical Theory and Method Abstracts by :
Download or read book Statistical Theory and Method Abstracts written by and published by . This book was released on 2001 with total page 750 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Sequential Analysis by : Alexander Tartakovsky
Download or read book Sequential Analysis written by Alexander Tartakovsky and published by CRC Press. This book was released on 2014-08-27 with total page 605 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sequential Analysis: Hypothesis Testing and Changepoint Detection systematically develops the theory of sequential hypothesis testing and quickest changepoint detection. It also describes important applications in which theoretical results can be used efficiently. The book reviews recent accomplishments in hypothesis testing and changepoint detection both in decision-theoretic (Bayesian) and non-decision-theoretic (non-Bayesian) contexts. The authors not only emphasize traditional binary hypotheses but also substantially more difficult multiple decision problems. They address scenarios with simple hypotheses and more realistic cases of two and finitely many composite hypotheses. The book primarily focuses on practical discrete-time models, with certain continuous-time models also examined when general results can be obtained very similarly in both cases. It treats both conventional i.i.d. and general non-i.i.d. stochastic models in detail, including Markov, hidden Markov, state-space, regression, and autoregression models. Rigorous proofs are given for the most important results. Written by leading authorities in the field, this book covers the theoretical developments and applications of sequential hypothesis testing and sequential quickest changepoint detection in a wide range of engineering and environmental domains. It explains how the theoretical aspects influence the hypothesis testing and changepoint detection problems as well as the design of algorithms.
Book Synopsis Inference, Asymptotics, and Applications by : Nancy Reid
Download or read book Inference, Asymptotics, and Applications written by Nancy Reid and published by World Scientific. This book was released on 2017-03-10 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book showcases the innovative research of Professor Skovgaard, by providing in one place a selection of his most important and influential papers. Introductions by colleagues set in context the highlights, key achievements, and impact, of each work. This book provides a survey of the field of asymptotic theory and inference as it was being pushed forward during an exceptionally fruitful time. It provides students and researchers with an overview of many aspects of the field.
Book Synopsis Mathematical Methods of Statistics by :
Download or read book Mathematical Methods of Statistics written by and published by . This book was released on 1999 with total page 616 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Abstracts of Communications written by and published by . This book was released on 1998 with total page 472 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Statistical Testing Strategies in the Health Sciences by : Albert Vexler
Download or read book Statistical Testing Strategies in the Health Sciences written by Albert Vexler and published by CRC Press. This book was released on 2017-12-19 with total page 703 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Testing Strategies in the Health Sciences provides a compendium of statistical approaches for decision making, ranging from graphical methods and classical procedures through computationally intensive bootstrap strategies to advanced empirical likelihood techniques. It bridges the gap between theoretical statistical methods and practical procedures applied to the planning and analysis of health-related experiments. The book is organized primarily based on the type of questions to be answered by inference procedures or according to the general type of mathematical derivation. It establishes the theoretical framework for each method, with a substantial amount of chapter notes included for additional reference. It then focuses on the practical application for each concept, providing real-world examples that can be easily implemented using corresponding statistical software code in R and SAS. The book also explains the basic elements and methods for constructing correct and powerful statistical decision-making processes to be adapted for complex statistical applications. With techniques spanning robust statistical methods to more computationally intensive approaches, this book shows how to apply correct and efficient testing mechanisms to various problems encountered in medical and epidemiological studies, including clinical trials. Theoretical statisticians, medical researchers, and other practitioners in epidemiology and clinical research will appreciate the book’s novel theoretical and applied results. The book is also suitable for graduate students in biostatistics, epidemiology, health-related sciences, and areas pertaining to formal decision-making mechanisms.
Book Synopsis Higher Order Asymptotics by : J. K. Ghosh
Download or read book Higher Order Asymptotics written by J. K. Ghosh and published by IMS. This book was released on 1994 with total page 126 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Asymptotic Optimal Inference for Non-ergodic Models by : I. V. Basawa
Download or read book Asymptotic Optimal Inference for Non-ergodic Models written by I. V. Basawa and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 183 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph contains a comprehensive account of the recent work of the authors and other workers on large sample optimal inference for non-ergodic models. The non-ergodic family of models can be viewed as an extension of the usual Fisher-Rao model for asymptotics, referred to here as an ergodic family. The main feature of a non-ergodic model is that the sample Fisher information, appropriately normed, converges to a non-degenerate random variable rather than to a constant. Mixture experiments, growth models such as birth processes, branching processes, etc. , and non-stationary diffusion processes are typical examples of non-ergodic models for which the usual asymptotics and the efficiency criteria of the Fisher-Rao-Wald type are not directly applicable. The new model necessitates a thorough review of both technical and qualitative aspects of the asymptotic theory. The general model studied includes both ergodic and non-ergodic families even though we emphasise applications of the latter type. The plan to write the monograph originally evolved through a series of lectures given by the first author in a graduate seminar course at Cornell University during the fall of 1978, and by the second author at the University of Munich during the fall of 1979. Further work during 1979-1981 on the topic has resolved many of the outstanding conceptual and technical difficulties encountered previously. While there are still some gaps remaining, it appears that the mainstream development in the area has now taken a more definite shape.
Book Synopsis Statistical Issues in Drug Research and Development by : Karl E. Peace
Download or read book Statistical Issues in Drug Research and Development written by Karl E. Peace and published by CRC Press. This book was released on 1989-12-11 with total page 390 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a compilation of topics addressed by the ASA Biopharmaceutical Section work groups, including the etiology and evolution of the work groups, the work group guidelines and structure, and the statistical issues associated with clinical trials in clinical drug development programs.
Book Synopsis Scientiae Mathematicae Japonicae by :
Download or read book Scientiae Mathematicae Japonicae written by and published by . This book was released on 2001 with total page 648 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Recent Advances in Econometrics and Statistics by : Matteo Barigozzi
Download or read book Recent Advances in Econometrics and Statistics written by Matteo Barigozzi and published by Springer Nature. This book was released on with total page 617 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Nonlinear Statistical Modeling by : Takeshi Amemiya
Download or read book Nonlinear Statistical Modeling written by Takeshi Amemiya and published by Cambridge University Press. This book was released on 2001-01-08 with total page 472 pages. Available in PDF, EPUB and Kindle. Book excerpt: This collection investigates parametric, semiparametric, nonparametric, and nonlinear estimation techniques in statistical modeling.
Book Synopsis Scientific and Technical Aerospace Reports by :
Download or read book Scientific and Technical Aerospace Reports written by and published by . This book was released on 1995 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: Lists citations with abstracts for aerospace related reports obtained from world wide sources and announces documents that have recently been entered into the NASA Scientific and Technical Information Database.
Book Synopsis Smooth Tests of Goodness of Fit by : J. C. W. Rayner
Download or read book Smooth Tests of Goodness of Fit written by J. C. W. Rayner and published by John Wiley & Sons. This book was released on 2009-07-23 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this fully revised and expanded edition of Smooth Tests of Goodness of Fit, the latest powerful techniques for assessing statistical and probabilistic models using this proven class of procedures are presented in a practical and easily accessible manner. Emphasis is placed on modern developments such as data-driven tests, diagnostic properties, and model selection techniques. Applicable to most statistical distributions, the methodology described in this book is optimal for deriving tests of fit for new distributions and complex probabilistic models, and is a standard against which new procedures should be compared. New features of the second edition include: Expansion of the methodology to cover virtually any statistical distribution, including exponential families Discussion and application of data-driven smooth tests Techniques for the selection of the best model for the data, with a guide to acceptable alternatives Numerous new, revised, and expanded examples, generated using R code Smooth Tests of Goodness of Fit is an invaluable resource for all methodological researchers as well as graduate students undertaking goodness-of-fit, statistical, and probabilistic model assessment courses. Practitioners wishing to make an informed choice of goodness-of-fit test will also find this book an indispensible guide. Reviews of the first edition: "This book gives a very readable account of the smooth tests of goodness of fit. The book can be read by scientists having only an introductory knowledge of statistics. It contains a fairly extensive list of references; research will find it helpful for the further development of smooth tests." --T.K. Chandra, Zentralblatt für Mathematik und ihre Grenzgebiete, Band 73, 1/92' "An excellent job of showing how smooth tests (a class of goodness of fit tests) are generally and easily applicable in assessing the validity of models involving statistical distributions....Highly recommended for undergraduate and graduate libraries." --Choice "The book can be read by scientists having only an introductory knowledge of statistics. It contains a fairly extensive list of references; researchers will find it helpful for the further development of smooth tests."--Mathematical Reviews "Very rich in examples . . . Should find its way to the desks of many statisticians." --Technometrics
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 Analysis of Mixed Effects Models by : Jiming Jiang
Download or read book Asymptotic Analysis of Mixed Effects Models written by Jiming Jiang and published by CRC Press. This book was released on 2017-09-19 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: Large sample techniques are fundamental to all fields of statistics. Mixed effects models, including linear mixed models, generalized linear mixed models, non-linear mixed effects models, and non-parametric mixed effects models are complex models, yet, these models are extensively used in practice. This monograph provides a comprehensive account of asymptotic analysis of mixed effects models. The monograph is suitable for researchers and graduate students who wish to learn about asymptotic tools and research problems in mixed effects models. It may also be used as a reference book for a graduate-level course on mixed effects models, or asymptotic analysis.
