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Introduction to empirical processes and semiparametric inference, Kosorok, Michael R.



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Цена: 15674р.
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Автор: Kosorok, Michael R.
Название:  Introduction to empirical processes and semiparametric inference
Издательство: Springer
Классификация:
ISBN: 0387749772
ISBN-13(EAN): 9780387749778
Обложка/Формат: Hardback
Страницы: 497
Вес: 0.898 кг.
Дата издания: 14.02.2008
Серия: Springer series in statistics
Язык: English
Издание: 2008 ed.
Иллюстрации: Xiv, 483 p.
Размер: 168 x 241 x 35
Читательская аудитория: Professional & vocational
Ссылка на Издательство: Link
Рейтинг:
Поставляется из: Германии
Описание: Presents an introduction to empirical processes and semi parametric inference. This book is suitable for statisticians, biostatisticians, and other researchers with a background in mathematical statistics who have an interest in learning about and doing research in empirical processes and semi parametric inference.



Causal Inference for Statistics, Social, and Biomedical Sciences

Автор: Imbens
Название: Causal Inference for Statistics, Social, and Biomedical Sciences
ISBN: 0521885884 ISBN-13(EAN): 9780521885881
Издательство: Cambridge Academ
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Цена: 5176 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

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.

An Introduction to Statistical Inference and Its Applications with R

Автор: Trosset
Название: An Introduction to Statistical Inference and Its Applications with R
ISBN: 1584889470 ISBN-13(EAN): 9781584889472
Издательство: Taylor&Francis
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Цена: 9239 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

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.

Introduction to Empirical Processes and Semiparametric Inference

Автор: Michael R. Kosorok
Название: Introduction to Empirical Processes and Semiparametric Inference
ISBN: 1441925783 ISBN-13(EAN): 9781441925787
Издательство: Springer
Рейтинг:
Цена: 17241 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Kosorok`s brilliant text provides a self-contained introduction to empirical processes and semiparametric inference. These powerful research techniques are surprisingly useful for developing methods of statistical inference for complex models and in understanding the properties of such methods.

Semiparametric Theory and Missing Data

Автор: Tsiatis
Название: Semiparametric Theory and Missing Data
ISBN: 0387324488 ISBN-13(EAN): 9780387324487
Издательство: Springer
Рейтинг:
Цена: 15674 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book summarizes current knowledge of the theory of estimation for semiparametric models with missing data, applying modern methods to missing, censored, and coarsened data with the goal of deriving estimators that are as robust and efficient as possible.

Semiparametric Regression

Автор: David Ruppert
Название: Semiparametric Regression
ISBN: 0521785162 ISBN-13(EAN): 9780521785167
Издательство: Cambridge Academ
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Цена: 4945 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Semiparametric regression is concerned with the flexible incorporation of non-linear functional relationships in regression analyses. Any application area that benefits from regression analysis can also benefit from semiparametric regression. Assuming only a basic familiarity with ordinary parametric regression, this user-friendly book explains the techniques and benefits of semiparametric regression in a concise and modular fashion. The authors make liberal use of graphics and examples plus case studies taken from environmental, financial, and other applications. They include practical advice on implementation and pointers to relevant software. The book is suitable as a textbook for students with little background in regression as well as a reference book for statistically oriented scientists such as biostatisticians, econometricians, quantitative social scientists, epidemiologists, with a good working knowledge of regression and the desire to begin using more flexible semiparametric models. Even experts on semiparametric regression should find something new here.

Efficient and Adaptive Estimation for Semiparametric Models

Автор: Bickel
Название: Efficient and Adaptive Estimation for Semiparametric Models
ISBN: 0387984739 ISBN-13(EAN): 9780387984735
Издательство: Springer
Цена: 11494 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: "Efficient and Adaptive Estimation for Semiparametric Models".

Nonparametric and Semiparametric Models

Автор: H?rdle
Название: Nonparametric and Semiparametric Models
ISBN: 3540207228 ISBN-13(EAN): 9783540207221
Издательство: Springer
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Цена: 16196 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: The concept of nonparametric smoothing is a central idea in statistics that aims to simultaneously estimate and modes the underlying structure. This book aims to present the statistical and mathematical principles of smoothing with a focus on applicable techniques.

Semiparametric Regression for the Social Sciences

Название: Semiparametric Regression for the Social Sciences
ISBN: 0470319917 ISBN-13(EAN): 9780470319918
Издательство: Wiley
Рейтинг:
Цена: 7017 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: An introductory guide to smoothing techniques, semiparametric estimators, and their related methods, this book describes the methodology via a selection of carefully explained examples and data sets. It also demonstrates the potential of these techniques using detailed empirical examples drawn from the social and political sciences.

Semiparametric Theory and Missing Data

Автор: Anastasios Tsiatis
Название: Semiparametric Theory and Missing Data
ISBN: 1441921850 ISBN-13(EAN): 9781441921857
Издательство: Springer
Рейтинг:
Цена: 17241 р.
Наличие на складе: Поставка под заказ.

Описание: This book summarizes current knowledge of the theory of estimation for semiparametric models with missing data, applying modern methods to missing, censored, and coarsened data with the goal of deriving estimators that are as robust and efficient as possible.

Methods for estimation and inference in modern econometrics

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: 9816 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.

Introduction to Probability and Statistical Inference

Автор: Roussas George G
Название: Introduction to Probability and Statistical Inference
ISBN: 0128001143 ISBN-13(EAN): 9780128001141
Издательство: Elsevier Science
Рейтинг:
Цена: 9400 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: An Introduction to Probability and Statistical Inference, Second Edition, guides you through probability models and statistical methods and helps you to think critically about various concepts. Written by award-winning author George Roussas, this book introduces readers with no prior knowledge in probability or statistics to a thinking process to help them obtain the best solution to a posed question or situation. It provides a plethora of examples for each topic discussed, giving the reader more experience in applying statistical methods to different situations. This text contains an enhanced number of exercises and graphical illustrations where appropriate to motivate the reader and demonstrate the applicability of probability and statistical inference in a great variety of human activities. Reorganized material is included in the statistical portion of the book to ensure continuity and enhance understanding. Each section includes relevant proofs where appropriate, followed by exercises with useful clues to their solutions. Furthermore, there are brief answers to even-numbered exercises at the back of the book and detailed solutions to all exercises are available to instructors in an Answers Manual. This text will appeal to advanced undergraduate and graduate students, as well as researchers and practitioners in engineering, business, social sciences or agriculture.

Concise Introduction to Statistical Inference

Автор: Thijssen Jacco
Название: Concise Introduction to Statistical Inference
ISBN: 1498755771 ISBN-13(EAN): 9781498755771
Издательство: Taylor&Francis
Рейтинг:
Цена: 6120 р.
Наличие на складе: Поставка под заказ.

Описание: This short book introduces the main ideas of statistical inference in a way that is both user friendly and mathematically sound. Particular emphasis is placed on the common foundation of many models used in practice. In addition, the book focuses on the formulation of appropriate statistical models to study problems in business, economics, and the social sciences, as well as on how to interpret the results from statistical analyses. The book will be useful to students who are interested in rigorous applications of statistics to problems in business, economics and the social sciences, as well as students who have studied statistics in the past, but need a more solid grounding in statistical techniques to further their careers. Jacco Thijssen is professor of finance at the University of York, UK. He holds a PhD in mathematical economics from Tilburg University, Netherlands. His main research interests are in applications of optimal stopping theory, stochastic calculus, and game theory to problems in economics and finance. Professor Thijssen has earned several awards for his statistics teaching.


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