Nonlinear Estimation and Classification, David D. Denison; Mark H. Hansen; Christopher C. H
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: David G. T. Denison Название: Bayesian Methods for Nonlinear Classification and Regression ISBN: 0471490369 ISBN-13(EAN): 9780471490364 Издательство: Wiley Рейтинг: Цена: 20584.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Regression analysis models the relationship between a set of responses and another variable: for example, to estimate the true position of a line through a number of observed points. Unfortunately, data rarely conforms to simple curves and straight lines - parametric models - and this text examines more complex - or nonparametric - models.
Автор: Rafael Mart?nez-Guerra; Christopher Diego Cruz-Anc Название: Algorithms of Estimation for Nonlinear Systems ISBN: 3319530399 ISBN-13(EAN): 9783319530390 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Preface.- Analysis of input-affine nonlinear processes.- Basic Definitions of Differential Algebras.- Algebraic Observability Condition for Nonlinear systems and External behaviour.- Generalized Observability Canonical Forms.- Observer Synthesis.- Tracking and Stabilization Problems.- Parametric and State Estimation.- Observer synthesis for a more general class of Nonlinear Systems.- A Separation Principle for Nonlinear Systems.- Some uncommon observers with interesting applications.- Appendix A Singularity Treatment.- Appendix B Some properties for Nonlinear Systems.
Автор: Gavin J.S. Ross Название: Nonlinear Estimation ISBN: 146128001X ISBN-13(EAN): 9781461280019 Издательство: Springer Рейтинг: Цена: 16070.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The book provides insights into why some models are difficult to fit, how to combine fits over different data sets, how to improve data collection to reduce prediction variance, and how to program particular models to handle a full range of data sets.
Автор: Joachim Inkmann Название: Conditional Moment Estimation of Nonlinear Equation Systems ISBN: 3540412077 ISBN-13(EAN): 9783540412076 Издательство: Springer Рейтинг: Цена: 11179.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Generalized method of moments (GMM) estimation of nonlinear systems has two important advantages over conventional maximum likelihood (ML) estimation: GMM estimation usually requires less restrictive distributional assumptions and remains computationally attractive when ML estimation becomes burdensome or even impossible.
Автор: Rudolph Kulhavy Название: Recursive Nonlinear Estimation ISBN: 3540760636 ISBN-13(EAN): 9783540760634 Издательство: Springer Рейтинг: Цена: 14365.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: In a close analogy to matching data in Euclidean space, this monograph views parameter estimation as matching of the empirical distribution of data with a model-based distribution. The book suggests a solution to the problem of recursive estimation of non-Gaussian and nonlinear models.
Описание: 22 papers on control of nonlinear partial differential equations highlight the area from a broad variety of viewpoints. A significant part of the volume is devoted to applications in engineering, continuum mechanics and population biology.
Описание: This book describes statistical techniques for the design and evaluation of research studies on medical diagnostic tests, screening tests, biomarkers and new technologies for classification and prediction in medicine.
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