Автор: Wilcox, Rand R. (university Of Southern California, Usa) Название: Introduction to robust estimation and hypothesis testing ISBN: 0128200987 ISBN-13(EAN): 9780128200988 Издательство: Elsevier Science Рейтинг: Цена: 16505.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Follow one girl as she builds a rocket and plans to take her friends on an amazing trip to the Sun and Moon. But will the task prove more difficult than she first thought? Imaginatively illustrated by T.S Spookytooth, this clever and inventive poem was written by eleven-year-old Collins Big Cat 2011 Writing Competition winner Nicole Sharrocks.
Автор: Alexandre B. Tsybakov Название: Introduction to Nonparametric Estimation ISBN: 0387790519 ISBN-13(EAN): 9780387790510 Издательство: Springer Рейтинг: Цена: 15372.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Presents basic nonparametric regression and density estimators and analyzes their properties. This book covers minimax lower bounds, and develops advanced topics such as: Pinsker`s theorem, oracle inequalities, Stein shrinkage, and sharp minimax adaptivity.
Описание: Bayesian Bounds provides a collection of the important papers dealing with the theory and application of Bayesian bounds. The book will be useful to both engineers and statisticians whether they are practicioners or theorists. The organization of the book and selection criteria is covered in the preface. Each part is introduced with the contributions of each selected paper and their interrelationship. Part 1contains a short history of Reverend Thomas Bayes and his classic paper that established the field. Part 2 contains the original derivation of the Bayesian Cramer-Rao bound and a simple derivation of the multiple parameter Bayesian CRB. Part 3 discusses global Bayesian bounds to provide broad coverage of this important area. Part 4 considers the case in which some of the parameters are deterministic and some are random. Hybrid Bayesian bounds are derived, as they are particularly important in the study of model mismatch problems. Part 5 considers generalized Cramer-Rao bounds. Part 6 discusses nonlinear stochastic dynamic systems. This type of system is a major component of most radar, sonar, and navigation systems. They are also encountered in nonlinear filtering problems. Applications of various Bayesian bounds to static parameter estimation problems are covered in Part 7 and to dynamic systems in Part 8. The book concludes with papers from the statistics literature that focus on Bayesian bounds in various models in Part 9.
Автор: Lehmann E.L., Casella George Название: Theory of Point Estimation ISBN: 0387985026 ISBN-13(EAN): 9780387985022 Издательство: Springer Рейтинг: Цена: 12577.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This second, much enlarged edition by Lehmann and Casella of Lehmann's classic text on point estimation maintains the outlook and general style of the first edition. All of the topics are updated. An entirely new chapter on Bayesian and hierarchical Bayesian approaches is provided, and there is much new material on simultaneous estimation. Each chapter concludes with a Notes section which contains suggestions for further study. The book is a companion volume to the second edition of Lehmann's "Testing Statistical Hypotheses".E.L. Lehmann is Professor Emeritus at the University of California, Berkeley. He is a member of the National Academy of Sciences and the American Academy of Arts and Sciences, and the recipient of honorary degrees from the University of Leiden, The Netherlands, and the University of Chicago.George Casella is the Liberty Hyde Bailey Professor of Biological Statistics in The College of Agriculture and Life Sciences at Cornell University. Casella has served as associate editor of The American Statistician, Statistical Science and JASA. He is currently the Theory and Methods Editor of JASA. Casella has authored two other textbooks (Statistical Inference, 1990, with Roger Berger and Variance Components, 1992, with Shayle A. Searle and Charles McCulloch). He is a fellow of the IMS and ASA, and an elected fellow of the ISI.Also available:E.L. Lehmann, Testing Statistical Hypotheses Second Edition, Springer-Verlag New York, Inc., ISBN 0-387-949194.
Автор: Pourahmadi Mohsen Название: High-dimensional Covariance Estimation ISBN: 1118034295 ISBN-13(EAN): 9781118034293 Издательство: Wiley Рейтинг: Цена: 12664.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Methods for estimating sparse and large covariance matrices Covariance and correlation matrices play fundamental roles in every aspect of the analysis of multivariate data collected from a variety of fields including business and economics, health care, engineering, and environmental and physical sciences.
Автор: Eric Gautier and Pierre Alquier Название: Inverse problems and high-dimensional estimation ISBN: 3642199887 ISBN-13(EAN): 9783642199882 Издательство: Springer Рейтинг: Цена: 15372.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The product of a high-flying summer school in Paris in 2009, this volume synthesises the state of the art on ill-posed statistical inverse problems and high-dimensional estimation and explores the ways these techniques can be applied to economics.
Автор: Gershon Eli Название: Advanced Topics in Control and Estimation of State-multiplic ISBN: 1447150694 ISBN-13(EAN): 9781447150695 Издательство: Springer Рейтинг: Цена: 15672.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides readers with a coherent, structured account of state-multiplicative noisy systems. It demonstrates practical control engineering examples from various areas of the discipline to illustrate the relevance of the theoretical development.
Автор: Efron Название: Large-Scale Inference ISBN: 110761967X ISBN-13(EAN): 9781107619678 Издательство: Cambridge Academ Рейтинг: Цена: 6811.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Modern scientific technology (such as microarrays and fMRI machines) produces data in vast quantities. Bradley Efron explains the empirical Bayes methods that help make sense of a new statistical world. This is essential reading for professional statisticians and graduate students wishing to use and understand important new techniques like false discovery rates.
Автор: Anatolyev, Stanislav Gospodinov, Nikolay Название: Methods for estimation and inference in modern econometrics ISBN: 1439838240 ISBN-13(EAN): 9781439838242 Издательство: Taylor&Francis Рейтинг: Цена: 15312.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Methods for Estimation and Inference in Modern Econometrics provides a comprehensive introduction to a wide range of emerging topics, such as generalized empirical likelihood estimation and alternative asymptotics under drifting parameterizations, which have not been discussed in detail outside of highly technical research papers. The book also addresses several problems often arising in the analysis of economic data, including weak identification, model misspecification, and possible nonstationarity. The book's appendix provides a review of some basic concepts and results from linear algebra, probability theory, and statistics that are used throughout the book.
Topics covered include:
Well-established nonparametric and parametric approaches to estimation and conventional (asymptotic and bootstrap) frameworks for statistical inference
Estimation of models based on moment restrictions implied by economic theory, including various method-of-moments estimators for unconditional and conditional moment restriction models, and asymptotic theory for correctly specified and misspecified models
Non-conventional asymptotic tools that lead to improved finite sample inference, such as higher-order asymptotic analysis that allows for more accurate approximations via various asymptotic expansions, and asymptotic approximations based on drifting parameter sequences
Offering a unified approach to studying econometric problems, Methods for Estimation and Inference in Modern Econometrics links most of the existing estimation and inference methods in a general framework to help readers synthesize all aspects of modern econometric theory. Various theoretical exercises and suggested solutions are included to facilitate understanding.
Автор: Srivastava, Virendera K. , Giles, David E.A. Название: Seemingly Unrelated Regression Equations Models ISBN: 0367451484 ISBN-13(EAN): 9780367451486 Издательство: Taylor&Francis Рейтинг: Цена: 6736.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book brings together the scattered literature associated with the seemingly unrelated regression equations (SURE) model used by econometricians and others. It focuses on the theoretical statistical results associated with the SURE model.
Автор: Gonin, Rene Название: Nonlinear Lp-Norm Estimation ISBN: 0367451166 ISBN-13(EAN): 9780367451165 Издательство: Taylor&Francis Рейтинг: Цена: 9492.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book delineates the history of Lp-norm estimation and examines the nonlinear Lp-norm estimation problem that is a viable alternative to least squares estimation problems. It is intended for both statisticians and applied mathematicians.
Описание: Nonresponse and other sources of bias are endemic features of public opinion surveys. We elaborate a general workflow of weighting-based survey inference, and describe in detail how this can be applied to the analysis of historical and contemporary opinion polls.
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