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Least Squares Regressions With The Bootstrap

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Least Squares Regressions With The Bootstrap

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Author : Jonas Böhmer
language : en
Publisher: GRIN Verlag
Release Date : 2009-09

Least Squares Regressions With The Bootstrap written by Jonas Böhmer and has been published by GRIN Verlag this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-09 with categories.

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.

Least Squares Regressions With The Bootstrap

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Author : Jonas Böhmer
language : en
Publisher: GRIN Verlag
Release Date : 2009-09-08

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.

Bootstrap Tests For Regression Models

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Author : L. Godfrey
language : en
Publisher: Springer
Release Date : 2009-07-29

Bootstrap Tests For Regression Models written by L. Godfrey and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-07-29 with Business & Economics categories.

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.

Practical Spreadsheet Modeling Using Risk

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Author : Dale Lehman
language : en
Publisher: CRC Press
Release Date : 2019-11-11

Practical Spreadsheet Modeling Using Risk written by Dale Lehman and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-11 with Business & Economics categories.

Practical Spreadsheet Modeling Using @Risk provides a guide of how to construct applied decision analysis models in spreadsheets. The focus is on the use of Monte Carlo simulation to provide quantitative assessment of uncertainties and key risk drivers. The book presents numerous examples based on real data and relevant practical decisions in a variety of settings, including health care, transportation, finance, natural resources, technology, manufacturing, retail, and sports and entertainment. All examples involve decision problems where uncertainties make simulation modeling useful to obtain decision insights and explore alternative choices. Good spreadsheet modeling practices are highlighted. The book is suitable for graduate students or advanced undergraduates in business, public policy, health care administration, or any field amenable to simulation modeling of decision problems. The book is also useful for applied practitioners seeking to build or enhance their spreadsheet modeling skills. Features Step-by-step examples of spreadsheet modeling and risk analysis in a variety of fields Description of probabilistic methods, their theoretical foundations, and their practical application in a spreadsheet environment Extensive example models and exercises based on real data and relevant decision problems Comprehensive use of the @Risk software for simulation analysis, including a free one-year educational software license

Bootstrap Methods

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Author : Michael R. Chernick
language : en
Publisher: John Wiley & Sons
Release Date : 2011-09-23

Bootstrap Methods written by Michael R. Chernick and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-09-23 with Mathematics categories.

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.

The Multiple Facets Of Partial Least Squares And Related Methods

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Author : Hervé Abdi
language : en
Publisher: Springer
Release Date : 2016-10-13

The Multiple Facets Of Partial Least Squares And Related Methods written by Hervé Abdi and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-10-13 with Mathematics categories.

This volume presents state of the art theories, new developments, and important applications of Partial Least Square (PLS) methods. The text begins with the invited communications of current leaders in the field who cover the history of PLS, an overview of methodological issues, and recent advances in regression and multi-block approaches. The rest of the volume comprises selected, reviewed contributions from the 8th International Conference on Partial Least Squares and Related Methods held in Paris, France, on 26-28 May, 2014. They are organized in four coherent sections: 1) new developments in genomics and brain imaging, 2) new and alternative methods for multi-table and path analysis, 3) advances in partial least square regression (PLSR), and 4) partial least square path modeling (PLS-PM) breakthroughs and applications. PLS methods are very versatile methods that are now used in areas as diverse as engineering, life science, sociology, psychology, brain imaging, genomics, and business among both academics and practitioners. The selected chapters here highlight this diversity with applied examples as well as the most recent advances.

Applied Regression Analysis And Generalized Linear Models

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Author : John Fox
language : en
Publisher: SAGE Publications
Release Date : 2015-03-18

Applied Regression Analysis And Generalized Linear Models written by John Fox and has been published by SAGE Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-03-18 with Social Science categories.

Combining a modern, data-analytic perspective with a focus on applications in the social sciences, the Third Edition of Applied Regression Analysis and Generalized Linear Models provides in-depth coverage of regression analysis, generalized linear models, and closely related methods, such as bootstrapping and missing data. Updated throughout, this Third Edition includes new chapters on mixed-effects models for hierarchical and longitudinal data. Although the text is largely accessible to readers with a modest background in statistics and mathematics, author John Fox also presents more advanced material in optional sections and chapters throughout the book. Accompanying website resources containing all answers to the end-of-chapter exercises. Answers to odd-numbered questions, as well as datasets and other student resources are available on the author′s website. NEW! Bonus chapter on Bayesian Estimation of Regression Models also available at the author′s website.

Bootstrap Confidence Regions In Regression Problems

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Author : Yvonne Elizabeth Pittelkow
language : en
Publisher:
Release Date : 1991

Bootstrap Confidence Regions In Regression Problems written by Yvonne Elizabeth Pittelkow and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1991 with Bootstrap (Statistics) categories.

Econometrics

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Author : Bruce Hansen
language : en
Publisher: Princeton University Press
Release Date : 2022-08-16

Econometrics written by Bruce Hansen and has been published by Princeton University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-16 with Business & Economics categories.

The most authoritative and up-to-date core econometrics textbook available Econometrics is the quantitative language of economic theory, analysis, and empirical work, and it has become a cornerstone of graduate economics programs. Econometrics provides graduate and PhD students with an essential introduction to this foundational subject in economics and serves as an invaluable reference for researchers and practitioners. This comprehensive textbook teaches fundamental concepts, emphasizes modern, real-world applications, and gives students an intuitive understanding of econometrics. Covers the full breadth of econometric theory and methods with mathematical rigor while emphasizing intuitive explanations that are accessible to students of all backgroundsDraws on integrated, research-level datasets, provided on an accompanying websiteDiscusses linear econometrics, time series, panel data, nonparametric methods, nonlinear econometric models, and modern machine learningFeatures hundreds of exercises that enable students to learn by doingIncludes in-depth appendices on matrix algebra and useful inequalities and a wealth of real-world examplesCan serve as a core textbook for a first-year PhD course in econometrics and as a follow-up to Bruce E. Hansen’s Probability and Statistics for Economists

Experimental Statistics And Data Analysis For Mechanical And Aerospace Engineers

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Author : James A. Middleton
language : en
Publisher: CRC Press
Release Date : 2021-11-25

Experimental Statistics And Data Analysis For Mechanical And Aerospace Engineers written by James A. Middleton and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-25 with Mathematics categories.

This book develops foundational concepts in probability and statistics with primary applications in mechanical and aerospace engineering. It develops the mindset a data analyst must have to interpret an ill-defined problem, operationalize it, collect or interpret data, and use this evidence to make decisions that can improve the quality of engineered products and systems. It was designed utilizing the latest research in statistics learning and in engagement teaching practices The author’s focus is on developing students’ conceptual understanding of statistical theory with the goal of effective design and conduct of experiments. Engineering statistics is primarily a form of data modeling. Emphasis is placed on modelling variation in observations, characterizing its distribution, and making inferences with regards to quality assurance and control. Fitting multivariate models, experimental design and hypothesis testing are all critical skills developed. All topics are developed utilizing real data from engineering projects, simulations, and laboratory experiences. In other words, we begin with data, we end with models. The key features are: Realistic contexts situating the learning of the statistics in actual engineering practice. A balance of rigorous mathematics, conceptual scaffolding, and real, messy data, to ensure that students learn the important concepts and can apply them in practice. The consistency of text, lecture notes, data sets, and simulations yield a coherent set of instructional resources for the instructor and a coherent set of learning experiences for the students. MatLab is used as a computational tool. Other tools are easily substituted. Table of Contents 1. Introduction 2. Dealing with Variation 3. Types of Data 4. Introduction to Probability 5. Sampling Distribution of the Mean 6. The Ten Building Blocks of Experimental Design 7. Sampling Distribution of the Proportion 8. Hypothesis Testing Using the 1-sample Statistics 9. 2-sample Statistics 10. Simple Linear Regression 11. The General Linear Model: Regression with Multiple Predictors 12. The GLM with Categorical Independent Variables: The Analysis of Variance 13. The General Linear Model: Randomized Block Factorial ANOVA 14. Factorial Analysis of Variance 15. The Bootstrap 16. Data Reduction: Principal Components Analysis Index Author Biography James A. Middleton is Professor of Mechanical and Aerospace Engineering and former Director of the Center for Research on Education in Science, Mathematics, Engineering, and Technology at Arizona State University. Previously, he held the Elmhurst Energy Chair in STEM education at the University of Birmingham in the UK. He received his Ph.D. from the University of Wisconsin-Madison. He has been Senior co-Chair of the Special Interest Group for Mathematics Education in the American Educational Research Association, and as Chair of the National Council of Teachers of Mathematics’ Research Committee. He has been a consultant for the College Board, the Rand Corporation, the National Academies, the American Statistical Association, the IEEE, and numerous school systems around the United States, the UK, and Australia. He has garnered over $30 million in grants to study and improve mathematics education in urban schools.

Least Squares Regressions With The Bootstrap

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