Solutions Manual to Accompany Modern Regression Methods 2e, Ryan
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: 102080.00 T 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: 137230.00 T 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: Simon J. Sheather Название: A Modern Approach to Regression with R ISBN: 0387096078 ISBN-13(EAN): 9780387096070 Издательство: Springer Рейтинг: Цена: 69870.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book focuses on tools and techniques for building regression models using real-world data and assessing their validity. A key theme throughout the book is that it makes sense to base inferences or conclusions only on valid models. The regression output and plots that appear throughout the book have been gen- ated using R.
Автор: Vittinghoff Название: Regression Methods in Biostatistics ISBN: 0387202757 ISBN-13(EAN): 9780387202754 Издательство: Springer Рейтинг: Цена: 75420.00 T Наличие на складе: Поставка под заказ. Описание: An introduction to the multipredictor regression methods widely used in biostatistics. This book covers linear models for continuous outcomes; logistic models for binary outcomes; the Cox model for right-censored survival times; repeated-measures models for longitudinal and hierarchical outcomes; and linear models for counts and other outcomes.
Автор: Wakefield Название: Bayesian and Frequentist Regression Methods ISBN: 1441909249 ISBN-13(EAN): 9781441909244 Издательство: Springer Рейтинг: Цена: 102480.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Bayesian and Frequentist Regression Methods provides a modern account of both Bayesian and frequentist methods of regression analysis.
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