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Author : Russell Davidson
Publisher :
ISBN 13 :
Total Pages : 24 pages
Book Rating : 4.:/5 (391 download)
Download or read book Bootstrap Test of Nonnested Linear Regression Models written by Russell Davidson and published by . This book was released on 1997 with total page 24 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : L. Godfrey
Publisher : Springer
ISBN 13 : 0230233732
Total Pages : 342 pages
Book Rating : 4.2/5 (32 download)
Download or read book Bootstrap Tests for Regression Models written by L. Godfrey and published by Springer. This book was released on 2009-07-29 with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Author : Russell Davidson
Publisher : Kingston, Ont. : Institute for Economic Research, Queen's University
ISBN 13 :
Total Pages : 24 pages
Book Rating : 4.:/5 (432 download)
Download or read book Bootstrap Tests of Nonnested Linear Regression Models written by Russell Davidson and published by Kingston, Ont. : Institute for Economic Research, Queen's University. This book was released on 1997 with total page 24 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Russell Davidson
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (535 download)
Download or read book Fast Double Bootstrap Tests of Nonnested Linear Regression Models written by Russell Davidson and published by . This book was released on 2003 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Gerhard Dikta
Publisher : Springer Nature
ISBN 13 : 3030734803
Total Pages : 256 pages
Book Rating : 4.0/5 (37 download)
Download or read book Bootstrap Methods written by Gerhard Dikta and published by Springer Nature. This book was released on 2021-08-10 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Author : Jonas Böhmer
Publisher : GRIN Verlag
ISBN 13 : 3640421833
Total Pages : 61 pages
Book Rating : 4.6/5 (44 download)
Download or read book Least Squares Regressions with the Bootstrap written by Jonas Böhmer and published by GRIN Verlag. This book was released on 2009-09 with total page 61 pages. Available in PDF, EPUB and Kindle. Book excerpt: Diploma Thesis from the year 2009 in the subject Statistics, grade: 1,6, University of Bonn (Statistische Abteilung der Rechts- und Staatswissenschaftlichen Fakult t), course: Diplomarbeit bei Prof.Dr. Alois Kneip, language: English, abstract: The statistical technique called bootstrap is usable with a lot of inferential problems and it is the main topic of this paper. Since the bootstrap provides material for a whole series of books it is essential to pick one special aspect of the bootstrap and investigate it in depth, otherwise the analysis would inevitably become too general. This aspect is the topic of regression. Hence, this paper will introduce the bootstrap and compare the performance of the new inference methods which it provides with some classical methods of judging a regression which were used in the years before the bootstrap. Therefore the remainder of this paper is as follows: First there will be a description of the basic model in which all of the following investigations will be done, chapter two. The next chapter will describe the different regression techniques which try to solve the model. The fourth chapter is going to show the behavior of these regression techniques in large samples, i.e. shows some classical methods of statistical inference. Following chapter five will give an introduction to the bootstrap which will be succeeded by a description of the bootstrap in regression problems, chapter six. The seventh chapter will show how inference is done with the help of the bootstrap. The eighth chapter is going to compare the performances of classical and bootstrap inference in regressions. Before the concluding remarks of chapter ten, there will be a practical application in chapter nine which tries to prove some observations of the preceeding chapters.
Author : Michael R. Chernick
Publisher : John Wiley & Sons
ISBN 13 : 1118211596
Total Pages : 337 pages
Book Rating : 4.1/5 (182 download)
Download or read book Bootstrap Methods written by Michael R. Chernick and published by John Wiley & Sons. This book was released on 2011-09-23 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Author : George Kapetanios
Publisher :
ISBN 13 :
Total Pages : 32 pages
Book Rating : 4.:/5 (593 download)
Download or read book Non-nested Models and the Likelihood Ratio Statistic written by George Kapetanios and published by . This book was released on 2003 with total page 32 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Jonas Böhmer
Publisher : GRIN Verlag
ISBN 13 : 3640422414
Total Pages : 54 pages
Book Rating : 4.6/5 (44 download)
Download or read book Least Squares Regressions with the Bootstrap written by Jonas Böhmer and published by GRIN Verlag. This book was released on 2009-09-08 with total page 54 pages. Available in PDF, EPUB and Kindle. Book excerpt: Diploma Thesis from the year 2009 in the subject Mathematics - Statistics, grade: 1,6, University of Bonn (Statistische Abteilung der Rechts- und Staatswissenschaftlichen Fakultät), course: Diplomarbeit bei Prof.Dr. Alois Kneip, language: English, abstract: The statistical technique called bootstrap is usable with a lot of inferential problems and it is the main topic of this paper. Since the bootstrap provides material for a whole series of books it is essential to pick one special aspect of the bootstrap and investigate it in depth, otherwise the analysis would inevitably become too general. This aspect is the topic of regression. Hence, this paper will introduce the bootstrap and compare the performance of the new inference methods which it provides with some classical methods of judging a regression which were used in the years before the bootstrap. Therefore the remainder of this paper is as follows: First there will be a description of the basic model in which all of the following investigations will be done, chapter two. The next chapter will describe the different regression techniques which try to solve the model. The fourth chapter is going to show the behavior of these regression techniques in large samples, i.e. shows some classical methods of statistical inference. Following chapter five will give an introduction to the bootstrap which will be succeeded by a description of the bootstrap in regression problems, chapter six. The seventh chapter will show how inference is done with the help of the bootstrap. The eighth chapter is going to compare the performances of classical and bootstrap inference in regressions. Before the concluding remarks of chapter ten, there will be a practical application in chapter nine which tries to prove some observations of the preceeding chapters.
Author : Michael J. Cullan
Publisher :
ISBN 13 :
Total Pages : 76 pages
Book Rating : 4.:/5 (118 download)
Download or read book Bootstrapped Information-theoretic Model Selection with Error Control (BITSEC) written by Michael J. Cullan and published by . This book was released on 2018 with total page 76 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical model selection using the Akaike Information Criterion (AIC) and similar criteria is a useful tool for comparing multiple and non-nested models without the specification of a null model, which has made it increasingly popular in the natural and social sciences. Despite their common usage, model selection methods are not driven by a notion of statistical confidence, so their results entail an unknown degree of uncertainty. This paper introduces a general framework which extends notions of Type-I and Type-II error to model selection. A theoretical method for controlling Type-I error using Difference of Goodness of Fit (DGOF) distributions is given, along with a bootstrap approach that approximates the procedure. Results are presented for simulated experiments using normal distributions, random walk models, nested linear regression, and nonnested regression including nonlinear models. Tests are performed using an R package developed by the author which will be made publicly available on journal publication of research results.
Author : Michael R. Chernick
Publisher : John Wiley & Sons
ISBN 13 : 1118625412
Total Pages : 318 pages
Book Rating : 4.1/5 (186 download)
Download or read book An Introduction to Bootstrap Methods with Applications to R written by Michael R. Chernick and published by John Wiley & Sons. This book was released on 2014-08-21 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive introduction to bootstrap methods in the R programming environment Bootstrap methods provide a powerful approach to statistical data analysis, as they have more general applications than standard parametric methods. An Introduction to Bootstrap Methods with Applications to R explores the practicality of this approach and successfully utilizes R to illustrate applications for the bootstrap and other resampling methods. This book provides a modern introduction to bootstrap methods for readers who do not have an extensive background in advanced mathematics. Emphasis throughout is on the use of bootstrap methods as an exploratory tool, including its value in variable selection and other modeling environments. The authors begin with a description of bootstrap methods and its relationship to other resampling methods, along with an overview of the wide variety of applications of the approach. Subsequent chapters offer coverage of improved confidence set estimation, estimation of error rates in discriminant analysis, and applications to a wide variety of hypothesis testing and estimation problems, including pharmaceutical, genomics, and economics. To inform readers on the limitations of the method, the book also exhibits counterexamples to the consistency of bootstrap methods. An introduction to R programming provides the needed preparation to work with the numerous exercises and applications presented throughout the book. A related website houses the book's R subroutines, and an extensive listing of references provides resources for further study. Discussing the topic at a remarkably practical and accessible level, An Introduction to Bootstrap Methods with Applications to R is an excellent book for introductory courses on bootstrap and resampling methods at the upper-undergraduate and graduate levels. It also serves as an insightful reference for practitioners working with data in engineering, medicine, and the social sciences who would like to acquire a basic understanding of bootstrap methods.
Author : L. G. Godfrey
Publisher :
ISBN 13 :
Total Pages : 21 pages
Book Rating : 4.:/5 (254 download)
Download or read book Tests of non-nested regression models : small sample adjustments and monte carlo evidence written by L. G. Godfrey and published by . This book was released on 1985 with total page 21 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Jean-Pierre Florens
Publisher : Cambridge University Press
ISBN 13 : 1139466771
Total Pages : 17 pages
Book Rating : 4.1/5 (394 download)
Download or read book Econometric Modeling and Inference written by Jean-Pierre Florens and published by Cambridge University Press. This book was released on 2007-07-02 with total page 17 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presents the main statistical tools of econometrics, focusing specifically on modern econometric methodology. The authors unify the approach by using a small number of estimation techniques, mainly generalized method of moments (GMM) estimation and kernel smoothing. The choice of GMM is explained by its relevance in structural econometrics and its preeminent position in econometrics overall. Split into four parts, Part I explains general methods. Part II studies statistical models that are best suited for microeconomic data. Part III deals with dynamic models that are designed for macroeconomic and financial applications. In Part IV the authors synthesize a set of problems that are specific to statistical methods in structural econometrics, namely identification and over-identification, simultaneity, and unobservability. Many theoretical examples illustrate the discussion and can be treated as application exercises. Nobel Laureate James A. Heckman offers a foreword to the work.
Author : Adriano Decarli
Publisher : Springer Science & Business Media
ISBN 13 : 1461236800
Total Pages : 352 pages
Book Rating : 4.4/5 (612 download)
Download or read book Statistical Modelling written by Adriano Decarli and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume constitutes the Proceedings of the joint meeting of GLIM89 and the 4th International Workshop on statistical Modelling, held in Trento, Italy, from 17 to 21 July 1989. The meeting aimed to bring together researchers interested in the development and application of generalized linear modelling in GLIM and those interested in statistical modelling in its widest sense. This joint meeting built upon the success of previous workshops held in Innsbruck, perugia and Vienna, and upon the two previous GLIM conferences , GLIM82 and GLIM85. The Proceedings of the latter two being available as numbers 14 and 32 in the springer Verlag series of Lecture Notes in Statistics). Much statistical modelling is carried out using GLIM, as is apparent from many of the papers in these Proceedings; however, the Programme Committee were also keen on encouraging papers which discussed more general modelling techniques. Thus about a third of the papers in this volume are outside the GLIM framework. The Programme Committee specifically requested non-theoretical papers in addition to considering theoretical contributions. Thus there are papers in a wide range of practical areas, such as radio spectral occupancy, comparison of birthweights, intervals between births, accidents of railway workers, genetics, demography, medical trials, the social sciences and insurance. A wide range of theoretical developments are discussed, for example, overdispersion, non-exponential family modelling, novel approaches to analysing contingency tables, random effects models, Kalman Filtering, model checking and extensions of Wedderburn's theoretical underpinning of GLMs.
Author : Peter Kennedy
Publisher : John Wiley & Sons
ISBN 13 : 1405182571
Total Pages : 608 pages
Book Rating : 4.4/5 (51 download)
Download or read book A Guide to Econometrics written by Peter Kennedy and published by John Wiley & Sons. This book was released on 2008-02-19 with total page 608 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dieses etwas andere Lehrbuch bietet keine vorgefertigten Rezepte und Problemlösungen, sondern eine kritische Diskussion ökonometrischer Modelle und Methoden: voller überraschender Fragen, skeptisch, humorvoll und anwendungsorientiert. Sein Erfolg gibt ihm Recht.
Author : Bryan F.J. Manly
Publisher : CRC Press
ISBN 13 : 1482296411
Total Pages : 468 pages
Book Rating : 4.4/5 (822 download)
Download or read book Randomization, Bootstrap and Monte Carlo Methods in Biology written by Bryan F.J. Manly and published by CRC Press. This book was released on 2018-10-03 with total page 468 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modern computer-intensive statistical methods play a key role in solving many problems across a wide range of scientific disciplines. This new edition of the bestselling Randomization, Bootstrap and Monte Carlo Methods in Biology illustrates the value of a number of these methods with an emphasis on biological applications. This textbook focuses on three related areas in computational statistics: randomization, bootstrapping, and Monte Carlo methods of inference. The author emphasizes the sampling approach within randomization testing and confidence intervals. Similar to randomization, the book shows how bootstrapping, or resampling, can be used for confidence intervals and tests of significance. It also explores how to use Monte Carlo methods to test hypotheses and construct confidence intervals. New to the Third Edition Updated information on regression and time series analysis, multivariate methods, survival and growth data as well as software for computational statistics References that reflect recent developments in methodology and computing techniques Additional references on new applications of computer-intensive methods in biology Providing comprehensive coverage of computer-intensive applications while also offering data sets online, Randomization, Bootstrap and Monte Carlo Methods in Biology, Third Edition supplies a solid foundation for the ever-expanding field of statistics and quantitative analysis in biology.
Author : L. G. Godfrey
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (137 download)
Download or read book Robust Non-Nested Testing for Ordinary Least Squares Regression When Some of the Regressors are Lagged Dependent Variables written by L. G. Godfrey and published by . This book was released on 2011 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The problem of testing non-nested regression models that include lagged values of the dependent variable as regressors is discussed. It is argued that it is essential to test for error autocorrelation if ordinary least squares and the associated J and F tests are to be used. A heteroskedasticity-robust joint test against a combination of the artificial alternatives used for autocorrelation and non-nested hypothesis tests is proposed. Monte Carlo results indicate that implementing this joint test using a wild bootstrap method leads to a well-behaved procedure and gives better control of finite sample significance levels than asymptotic critical values.
