Author: Russell DavidsonPublisher: Kingston, Ont. : Institute for Economic Research, Queen's University
ISBN:
Category :
Languages : en
Pages : 24
Book Description
Bootstrap Tests of Nonnested Linear Regression Models
Author: Russell DavidsonPublisher: Kingston, Ont. : Institute for Economic Research, Queen's University
ISBN:
Category :
Languages : en
Pages : 24
Book Description
Fast Double Bootstrap Tests of Nonnested Linear Regression Models
Author: Russell DavidsonBootstrap Test of Nonnested Linear Regression Models
Author: Russell DavidsonPublisher:
ISBN:
Category : Bootstrap (Statistics)
Languages : en
Pages : 24
Book Description
Bootstrap Tests for Regression Models
Author: L. GodfreyPublisher: Springer
ISBN: 0230233732
Category : Business & Economics
Languages : en
Pages : 342
Book Description
An accessible discussion examining computationally-intensive techniques and bootstrap methods, providing ways to improve the finite-sample performance of well-known asymptotic tests for regression models. This book uses the linear regression model as a framework for introducing simulation-based tests to help perform econometric analyses.
Bootstrap Methods
Author: Gerhard DiktaPublisher: Springer Nature
ISBN: 3030734803
Category : Mathematics
Languages : en
Pages : 256
Book Description
This book provides a compact introduction to the bootstrap method. In addition to classical results on point estimation and test theory, multivariate linear regression models and generalized linear models are covered in detail. Special attention is given to the use of bootstrap procedures to perform goodness-of-fit tests to validate model or distributional assumptions. In some cases, new methods are presented here for the first time. The text is motivated by practical examples and the implementations of the corresponding algorithms are always given directly in R in a comprehensible form. Overall, R is given great importance throughout. Each chapter includes a section of exercises and, for the more mathematically inclined readers, concludes with rigorous proofs. The intended audience is graduate students who already have a prior knowledge of probability theory and mathematical statistics.
Non-nested Models and the Likelihood Ratio Statistic
Author: George KapetaniosPublisher:
ISBN:
Category : Statistics
Languages : en
Pages : 32
Book Description
Bootstrap Tests for the Error Distribution in Linear and Nonparametric Regression Models
Author: Natalie NeumeyerBootstrap Methods
Author: Michael R. ChernickPublisher: John Wiley & Sons
ISBN: 1118211596
Category : Mathematics
Languages : en
Pages : 337
Book Description
A practical and accessible introduction to the bootstrap method——newly revised and updated Over the past decade, the application of bootstrap methods to new areas of study has expanded, resulting in theoretical and applied advances across various fields. Bootstrap Methods, Second Edition is a highly approachable guide to the multidisciplinary, real-world uses of bootstrapping and is ideal for readers who have a professional interest in its methods, but are without an advanced background in mathematics. Updated to reflect current techniques and the most up-to-date work on the topic, the Second Edition features: The addition of a second, extended bibliography devoted solely to publications from 1999–2007, which is a valuable collection of references on the latest research in the field A discussion of the new areas of applicability for bootstrap methods, including use in the pharmaceutical industry for estimating individual and population bioequivalence in clinical trials A revised chapter on when and why bootstrap fails and remedies for overcoming these drawbacks Added coverage on regression, censored data applications, P-value adjustment, ratio estimators, and missing data New examples and illustrations as well as extensive historical notes at the end of each chapter With a strong focus on application, detailed explanations of methodology, and complete coverage of modern developments in the field, Bootstrap Methods, Second Edition is an indispensable reference for applied statisticians, engineers, scientists, clinicians, and other practitioners who regularly use statistical methods in research. It is also suitable as a supplementary text for courses in statistics and resampling methods at the upper-undergraduate and graduate levels.
Bootstraptests in Linear Models with Many Regressors
Author: Patrick RichardPublisher:
ISBN:
Category :
Languages : en
Pages :
Book Description
This paper is concerned with bootstrap hypothesis testing in high dimensional linear regression models. Using a theoretical framework recently introduced by Anatolyev (2012), we show that bootstrap F, LR and LM tests are asymptotically valid even when the numbers of estimated parameters and tested restrictions are not asymptotically negligible fractions of the sample size. These results are derived for models with iid error terms, but Monte Carlo evidence suggests that they extend to the wild bootstrap in the presence of heteroskedasticity and to bootstrap methods for heavy tailed data.
Author: L. G. Godfrey