Methods for estimation and inference in modern econometrics, Anatolyev, Stanislav Gospodinov, Nikolay
Автор: Boos Название: Essential Statistical Inference ISBN: 1461448174 ISBN-13(EAN): 9781461448174 Издательство: Springer Рейтинг: Цена: 16334 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A superb resource on statistical inference for researchers or students, this book has R code throughout, including in sample problems, and an appendix of derived notation and formulae. It covers core topics as well as modern aspects such as M-estimation.
Описание: Most questions in social and biomedical sciences are causal in nature: what would happen to individuals, or to groups, if part of their environment were changed? In this groundbreaking text, two world-renowned experts present statistical methods for studying such questions. This book starts with the notion of potential outcomes, each corresponding to the outcome that would be realized if a subject were exposed to a particular treatment or regime. In this approach, causal effects are comparisons of such potential outcomes. The fundamental problem of causal inference is that we can only observe one of the potential outcomes for a particular subject. The authors discuss how randomized experiments allow us to assess causal effects and then turn to observational studies. They lay out the assumptions needed for causal inference and describe the leading analysis methods, including matching, propensity-score methods, and instrumental variables. Many detailed applications are included, with special focus on practical aspects for the empirical researcher.
Автор: Edited by Roberto Mariano Название: Simulation-based Inference in Econometrics ISBN: 0521591120 ISBN-13(EAN): 9780521591126 Издательство: Cambridge Academ Рейтинг: Цена: 17716 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This substantial volume has two principal objectives. First it provides an overview of the statistical foundations of Simulation-based inference. This includes the summary and synthesis of the many concepts and results extant in the theoretical literature, the different classes of problems and estimators, the asymptotic properties of these estimators, as well as descriptions of the different simulators in use. Second, the volume provides empirical and operational examples of SBI methods. Often what is missing, even in existing applied papers, are operational issues. Which simulator works best for which problem and why? This volume will explicitly address the important numerical and computational issues in SBI which are not covered comprehensively in the existing literature. Examples of such issues are: comparisons with existing tractable methods, number of replications needed for robust results, choice of instruments, simulation noise and bias as well as efficiency loss in practice.
Автор: Mariano, Roberto S. Название: Simulation-based Inference in Econometrics ISBN: 052108802X ISBN-13(EAN): 9780521088022 Издательство: Cambridge Academ Рейтинг: Цена: 6325 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: An overview of the techniques and practices involved in simulation-based inference.
Автор: Millar, Russell Название: Maximum likelihood estimation and inference ISBN: 0470094826 ISBN-13(EAN): 9780470094822 Издательство: Wiley Рейтинг: Цена: 14520 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Applied Likelihood Methods provides an accessible and practical introduction to likelihood modeling, supported by examples and software. The book features applications from a range of disciplines, including statistics, medicine, biology, and ecology.
Описание: Filling a longstanding need in the physical sciences, Bayesian Inference offers the first basic introduction for advanced undergraduates and graduates in the physical sciences. This text and reference generalizes Gaussian error intervals to situations in which the data follow distributions other than Gaussian. This usually occurs in frontier science because the observed parameter is barely above the background or the histogram of multiparametric data contains many empty bins. In this case, the determination of the validity of a theory cannot be based on the chi-squared-criterion. In addition to the solutions of practical problems, this approach provides an epistemic insight: the logic of quantum mechanics is obtained as the logic of unbiased inference from counting data. Requiring no knowledge of quantum mechanics, the text is written on introductory level, with many examples and exercises, for physicists planning to, or working in, fields such as medical physics, nuclear physics, quantum mechanics, and chaos.
Описание: In 1982, Springer published the English translation of the Russian book Estimation of Dependencies Based on Empirical Data which became the foundation of the statistical theory of learning and generalization (the VC theory). A number of new principles and new technologies of learning, including SVM technology, have been developed based on this theory.The second edition of this book contains two parts:- A reprint of the first edition which provides the classical foundation of Statistical Learning Theory- Four new chapters describing the latest ideas in the development of statistical inference methods. They form the second part of the book entitled Empirical Inference ScienceThe second part of the book discusses along with new models of inference the general philosophical principles of making inferences from observations. It includes new paradigms of inference that use non-inductive methods appropriate for a complex world, in contrast to inductive methods of inference developed in the classical philosophy of science for a simple world.The two parts of the book cover a wide spectrum of ideas related to the essence of intelligence: from the rigorous statistical foundation of learning models to broad philosophical imperatives for generalization.The book is intended for researchers who deal with a variety of problems in empirical inference: statisticians, mathematicians, physicists, computer scientists, and philosophers.
Автор: Liu Название: Simultaneous Inference in Regression ISBN: 1439828091 ISBN-13(EAN): 9781439828090 Издательство: Taylor&Francis Рейтинг: Цена: 32670 р. Наличие на складе: Поставка под заказ.
Описание: With examples and MATLAB® programs that make it easy to apply the methods to your own data analysis, this book provides a thorough overview of the construction methods and applications of simultaneous confidence bands for various inferential purposes. Most of the text covers normal-error linear regression models, although the author also describes the logistic regression model to show how simultaneous confidence bands can be constructed and used for generalized linear regression models. The MATLAB programs, along with color figures, are available for download on the author’s website.
Описание: With amusing anecdotes and trivia, this text explains how statistical methods are used for data analysis and uses the elementary functions of R to perform the individual steps of statistical procedures. It introduces basic concepts of inference through a careful study of several important procedures, including parametric and nonparametric methods, analysis of variance, and regression. The text also presents many applications, supporting data sets, and end-of-chapter exercises. The R code and data sets are available for download online and a solutions manual is available for qualifying instructors.
Автор: Basu Название: Statistical Inference ISBN: 1420099655 ISBN-13(EAN): 9781420099652 Издательство: Taylor&Francis Рейтинг: Цена: 25410 р. Наличие на складе: Невозможна поставка.
Описание: This book gives a comprehensive account of density-based minimum distance methods and their use in statistical inference. It covers statistical distances, density-based minimum distance methods, discrete and continuous models, asymptotic distributions, robustness, computational issues, residual adjustment functions, graphical descriptions of robustness, penalized and combined distances, multisample methods, weighted likelihood, and multinomial goodness-of-fit tests. The book also introduces the minimum distance methodology in interdisciplinary areas, such as neural networks and image processing, as well as specialized models and problems, including regression, mixture models, survival and Bayesian analysis, and more.
Описание: 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.
Название: Nonparametric inference ISBN: 981270034X ISBN-13(EAN): 9789812700346 Издательство: World Scientific Publishing Рейтинг: Цена: 27116 р. Наличие на складе: Поставка под заказ.
Описание: This book provides a solid foundation on nonparametric inference for students taking a graduate course in nonparametric statistics and serves as an easily
accessible source for researchers in the area. With the exception of some sections requiring familiarity with measure theory, readers with an advanced calculus background will be
comfortable with the material.
ООО "Логосфера " Тел:+7(495) 980-12-10 www.logobook.ru