Author: Gökhan Gül
Publisher: Springer
ISBN: 3319492861
Category : Technology & Engineering
Languages : en
Pages : 156
Book Description
This book generalizes and extends the available theory in robust and decentralized hypothesis testing. In particular, it presents a robust test for modeling errors which is independent from the assumptions that a sufficiently large number of samples is available, and that the distance is the KL-divergence. Here, the distance can be chosen from a much general model, which includes the KL-divergence as a very special case. This is then extended by various means. A minimax robust test that is robust against both outliers as well as modeling errors is presented. Minimax robustness properties of the given tests are also explicitly proven for fixed sample size and sequential probability ratio tests. The theory of robust detection is extended to robust estimation and the theory of robust distributed detection is extended to classes of distributions, which are not necessarily stochastically bounded. It is shown that the quantization functions for the decision rules can also be chosen as non-monotone. Finally, the book describes the derivation of theoretical bounds in minimax decentralized hypothesis testing, which have not yet been known. As a timely report on the state-of-the-art in robust hypothesis testing, this book is mainly intended for postgraduates and researchers in the field of electrical and electronic engineering, statistics and applied probability. Moreover, it may be of interest for students and researchers working in the field of classification, pattern recognition and cognitive radio.
Robust and Distributed Hypothesis Testing
Author: Gökhan Gül
Publisher: Springer
ISBN: 3319492861
Category : Technology & Engineering
Languages : en
Pages : 156
Book Description
This book generalizes and extends the available theory in robust and decentralized hypothesis testing. In particular, it presents a robust test for modeling errors which is independent from the assumptions that a sufficiently large number of samples is available, and that the distance is the KL-divergence. Here, the distance can be chosen from a much general model, which includes the KL-divergence as a very special case. This is then extended by various means. A minimax robust test that is robust against both outliers as well as modeling errors is presented. Minimax robustness properties of the given tests are also explicitly proven for fixed sample size and sequential probability ratio tests. The theory of robust detection is extended to robust estimation and the theory of robust distributed detection is extended to classes of distributions, which are not necessarily stochastically bounded. It is shown that the quantization functions for the decision rules can also be chosen as non-monotone. Finally, the book describes the derivation of theoretical bounds in minimax decentralized hypothesis testing, which have not yet been known. As a timely report on the state-of-the-art in robust hypothesis testing, this book is mainly intended for postgraduates and researchers in the field of electrical and electronic engineering, statistics and applied probability. Moreover, it may be of interest for students and researchers working in the field of classification, pattern recognition and cognitive radio.
Publisher: Springer
ISBN: 3319492861
Category : Technology & Engineering
Languages : en
Pages : 156
Book Description
This book generalizes and extends the available theory in robust and decentralized hypothesis testing. In particular, it presents a robust test for modeling errors which is independent from the assumptions that a sufficiently large number of samples is available, and that the distance is the KL-divergence. Here, the distance can be chosen from a much general model, which includes the KL-divergence as a very special case. This is then extended by various means. A minimax robust test that is robust against both outliers as well as modeling errors is presented. Minimax robustness properties of the given tests are also explicitly proven for fixed sample size and sequential probability ratio tests. The theory of robust detection is extended to robust estimation and the theory of robust distributed detection is extended to classes of distributions, which are not necessarily stochastically bounded. It is shown that the quantization functions for the decision rules can also be chosen as non-monotone. Finally, the book describes the derivation of theoretical bounds in minimax decentralized hypothesis testing, which have not yet been known. As a timely report on the state-of-the-art in robust hypothesis testing, this book is mainly intended for postgraduates and researchers in the field of electrical and electronic engineering, statistics and applied probability. Moreover, it may be of interest for students and researchers working in the field of classification, pattern recognition and cognitive radio.
Introduction to Robust Estimation and Hypothesis Testing
Author: Rand R. Wilcox
Publisher: Academic Press
ISBN: 0123869838
Category : Mathematics
Languages : en
Pages : 713
Book Description
"This book focuses on the practical aspects of modern and robust statistical methods. The increased accuracy and power of modern methods, versus conventional approaches to the analysis of variance (ANOVA) and regression, is remarkable. Through a combination of theoretical developments, improved and more flexible statistical methods, and the power of the computer, it is now possible to address problems with standard methods that seemed insurmountable only a few years ago"--
Publisher: Academic Press
ISBN: 0123869838
Category : Mathematics
Languages : en
Pages : 713
Book Description
"This book focuses on the practical aspects of modern and robust statistical methods. The increased accuracy and power of modern methods, versus conventional approaches to the analysis of variance (ANOVA) and regression, is remarkable. Through a combination of theoretical developments, improved and more flexible statistical methods, and the power of the computer, it is now possible to address problems with standard methods that seemed insurmountable only a few years ago"--
Robust and Distributed Hypothesis Testing
Author: Gökhan Gül
Publisher:
ISBN: 9783319492872
Category : Mathematical statistics
Languages : en
Pages : 141
Book Description
Publisher:
ISBN: 9783319492872
Category : Mathematical statistics
Languages : en
Pages : 141
Book Description
Robust Estimation and Hypothesis Testing
Author: Moti Lal Tiku
Publisher: New Age International
ISBN: 8122415563
Category : Estimation theory
Languages : en
Pages : 22
Book Description
In statistical theory and practice, a certain distribution is usually assumed and then optimal solutions sought. Since deviations from an assumed distribution are very common, one cannot feel comfortable with assuming a particular distribution and believing it to be exactly correct. That brings the robustness issue in focus. In this book, we have given statistical procedures which are robust to plausible deviations from an assumed mode. The method of modified maximum likelihood estimation is used in formulating these procedures. The modified maximum likelihood estimators are explicit functions of sample observations and are easy to compute. They are asymptotically fully efficient and are as efficient as the maximum likelihood estimators for small sample sizes. The maximum likelihood estimators have computational problems and are, therefore, elusive. A broad range of topics are covered in this book. Solutions are given which are easy to implement and are efficient. The solutions are also robust to data anomalies: outliers, inliers, mixtures and data contaminations. Numerous real life applications of the methodology are given.
Publisher: New Age International
ISBN: 8122415563
Category : Estimation theory
Languages : en
Pages : 22
Book Description
In statistical theory and practice, a certain distribution is usually assumed and then optimal solutions sought. Since deviations from an assumed distribution are very common, one cannot feel comfortable with assuming a particular distribution and believing it to be exactly correct. That brings the robustness issue in focus. In this book, we have given statistical procedures which are robust to plausible deviations from an assumed mode. The method of modified maximum likelihood estimation is used in formulating these procedures. The modified maximum likelihood estimators are explicit functions of sample observations and are easy to compute. They are asymptotically fully efficient and are as efficient as the maximum likelihood estimators for small sample sizes. The maximum likelihood estimators have computational problems and are, therefore, elusive. A broad range of topics are covered in this book. Solutions are given which are easy to implement and are efficient. The solutions are also robust to data anomalies: outliers, inliers, mixtures and data contaminations. Numerous real life applications of the methodology are given.
Introduction to Robust Estimation and Hypothesis Testing
Author: Rand R. Wilcox
Publisher: Academic Press
ISBN: 0127515429
Category : Mathematics
Languages : en
Pages : 610
Book Description
This revised book provides a thorough explanation of the foundation of robust methods, incorporating the latest updates on R and S-Plus, robust ANOVA (Analysis of Variance) and regression. It guides advanced students and other professionals through the basic strategies used for developing practical solutions to problems, and provides a brief background on the foundations of modern methods, placing the new methods in historical context. Author Rand Wilcox includes chapter exercises and many real-world examples that illustrate how various methods perform in different situations. Introduction to Robust Estimation and Hypothesis Testing, Second Edition, focuses on the practical applications of modern, robust methods which can greatly enhance our chances of detecting true differences among groups and true associations among variables. * Covers latest developments in robust regression * Covers latest improvements in ANOVA * Includes newest rank-based methods * Describes and illustrated easy to use software
Publisher: Academic Press
ISBN: 0127515429
Category : Mathematics
Languages : en
Pages : 610
Book Description
This revised book provides a thorough explanation of the foundation of robust methods, incorporating the latest updates on R and S-Plus, robust ANOVA (Analysis of Variance) and regression. It guides advanced students and other professionals through the basic strategies used for developing practical solutions to problems, and provides a brief background on the foundations of modern methods, placing the new methods in historical context. Author Rand Wilcox includes chapter exercises and many real-world examples that illustrate how various methods perform in different situations. Introduction to Robust Estimation and Hypothesis Testing, Second Edition, focuses on the practical applications of modern, robust methods which can greatly enhance our chances of detecting true differences among groups and true associations among variables. * Covers latest developments in robust regression * Covers latest improvements in ANOVA * Includes newest rank-based methods * Describes and illustrated easy to use software
Testing For Normality
Author: Henry C. Thode
Publisher: CRC Press
ISBN: 9780203910894
Category : Mathematics
Languages : en
Pages : 506
Book Description
Describes the selection, design, theory, and application of tests for normality. Covers robust estimation, test power, and univariate and multivariate normality. Contains tests ofr multivariate normality and coordinate-dependent and invariant approaches.
Publisher: CRC Press
ISBN: 9780203910894
Category : Mathematics
Languages : en
Pages : 506
Book Description
Describes the selection, design, theory, and application of tests for normality. Covers robust estimation, test power, and univariate and multivariate normality. Contains tests ofr multivariate normality and coordinate-dependent and invariant approaches.
Learning Statistics with R
Author: Daniel Navarro
Publisher: Lulu.com
ISBN: 1326189727
Category : Computers
Languages : en
Pages : 617
Book Description
"Learning Statistics with R" covers the contents of an introductory statistics class, as typically taught to undergraduate psychology students, focusing on the use of the R statistical software and adopting a light, conversational style throughout. The book discusses how to get started in R, and gives an introduction to data manipulation and writing scripts. From a statistical perspective, the book discusses descriptive statistics and graphing first, followed by chapters on probability theory, sampling and estimation, and null hypothesis testing. After introducing the theory, the book covers the analysis of contingency tables, t-tests, ANOVAs and regression. Bayesian statistics are covered at the end of the book. For more information (and the opportunity to check the book out before you buy!) visit http://ua.edu.au/ccs/teaching/lsr or http://learningstatisticswithr.com
Publisher: Lulu.com
ISBN: 1326189727
Category : Computers
Languages : en
Pages : 617
Book Description
"Learning Statistics with R" covers the contents of an introductory statistics class, as typically taught to undergraduate psychology students, focusing on the use of the R statistical software and adopting a light, conversational style throughout. The book discusses how to get started in R, and gives an introduction to data manipulation and writing scripts. From a statistical perspective, the book discusses descriptive statistics and graphing first, followed by chapters on probability theory, sampling and estimation, and null hypothesis testing. After introducing the theory, the book covers the analysis of contingency tables, t-tests, ANOVAs and regression. Bayesian statistics are covered at the end of the book. For more information (and the opportunity to check the book out before you buy!) visit http://ua.edu.au/ccs/teaching/lsr or http://learningstatisticswithr.com
Communication Research Statistics
Author: John C. Reinard
Publisher: SAGE Publications
ISBN: 1506320481
Category : Language Arts & Disciplines
Languages : en
Pages : 604
Book Description
"While most books on statistics seem to be written as though targeting other statistics professors, John Reinard′s Communication Research Statistics is especially impressive because it is clearly intended for the student reader, filled with unusually clear explanations and with illustrations on the use of SPSS. I enjoyed reading this lucid, student-friendly book and expect students will benefit enormously from its content and presentation. Well done!" --John C. Pollock, The College of New Jersey Written in an accessible style using straightforward and direct language, Communication Research Statistics guides students through the statistics actually used in most empirical research undertaken in communication studies. This introductory textbook is the only work in communication that includes details on statistical analysis of data with a full set of data analysis instructions based on SPSS 12 and Excel XP. Key Features: Emphasizes basic and introductory statistical thinking: The basic needs of novice researchers and students are addressed, while underscoring the foundational elements of statistical analyses in research. Students learn how statistics are used to provide evidence for research arguments and how to evaluate such evidence for themselves. Prepares students to use statistics: Students are encouraged to use statistics as they encounter and evaluate quantitative research. The book details how statistics can be understood by developing actual skills to carry out rudimentary work. Examples are drawn from mass communication, speech communication, and communication disorders. Incorporates SPSS 12 and Excel: A distinguishing feature is the inclusion of coverage of data analysis by use of SPSS 12 and by Excel. Information on the use of major computer software is designed to let students use such tools immediately. Companion Web Site! A dedicated Web site includes a glossary, data sets, chapter summaries, additional readings, links to other useful sites, selected "calculators" for computation of related statistics, additional macros for selected statistics using Excel and SPSS, and extra chapters on multiple discriminant analysis and loglinear analysis. Intended Audience: Ideal for undergraduate and graduate courses in Communication Research Statistics or Methods; also relevant for many Research Methods courses across the social sciences
Publisher: SAGE Publications
ISBN: 1506320481
Category : Language Arts & Disciplines
Languages : en
Pages : 604
Book Description
"While most books on statistics seem to be written as though targeting other statistics professors, John Reinard′s Communication Research Statistics is especially impressive because it is clearly intended for the student reader, filled with unusually clear explanations and with illustrations on the use of SPSS. I enjoyed reading this lucid, student-friendly book and expect students will benefit enormously from its content and presentation. Well done!" --John C. Pollock, The College of New Jersey Written in an accessible style using straightforward and direct language, Communication Research Statistics guides students through the statistics actually used in most empirical research undertaken in communication studies. This introductory textbook is the only work in communication that includes details on statistical analysis of data with a full set of data analysis instructions based on SPSS 12 and Excel XP. Key Features: Emphasizes basic and introductory statistical thinking: The basic needs of novice researchers and students are addressed, while underscoring the foundational elements of statistical analyses in research. Students learn how statistics are used to provide evidence for research arguments and how to evaluate such evidence for themselves. Prepares students to use statistics: Students are encouraged to use statistics as they encounter and evaluate quantitative research. The book details how statistics can be understood by developing actual skills to carry out rudimentary work. Examples are drawn from mass communication, speech communication, and communication disorders. Incorporates SPSS 12 and Excel: A distinguishing feature is the inclusion of coverage of data analysis by use of SPSS 12 and by Excel. Information on the use of major computer software is designed to let students use such tools immediately. Companion Web Site! A dedicated Web site includes a glossary, data sets, chapter summaries, additional readings, links to other useful sites, selected "calculators" for computation of related statistics, additional macros for selected statistics using Excel and SPSS, and extra chapters on multiple discriminant analysis and loglinear analysis. Intended Audience: Ideal for undergraduate and graduate courses in Communication Research Statistics or Methods; also relevant for many Research Methods courses across the social sciences
Robustness Tests for Quantitative Research
Author: Eric Neumayer
Publisher: Cambridge University Press
ISBN: 1108415393
Category : Business & Economics
Languages : en
Pages : 269
Book Description
This highly accessible book presents robustness testing as the methodology for conducting quantitative analyses in the presence of model uncertainty.
Publisher: Cambridge University Press
ISBN: 1108415393
Category : Business & Economics
Languages : en
Pages : 269
Book Description
This highly accessible book presents robustness testing as the methodology for conducting quantitative analyses in the presence of model uncertainty.
Understanding Statistics and Experimental Design
Author: Michael H. Herzog
Publisher: Springer
ISBN: 3030034992
Category : Science
Languages : en
Pages : 146
Book Description
This open access textbook provides the background needed to correctly use, interpret and understand statistics and statistical data in diverse settings. Part I makes key concepts in statistics readily clear. Parts I and II give an overview of the most common tests (t-test, ANOVA, correlations) and work out their statistical principles. Part III provides insight into meta-statistics (statistics of statistics) and demonstrates why experiments often do not replicate. Finally, the textbook shows how complex statistics can be avoided by using clever experimental design. Both non-scientists and students in Biology, Biomedicine and Engineering will benefit from the book by learning the statistical basis of scientific claims and by discovering ways to evaluate the quality of scientific reports in academic journals and news outlets.
Publisher: Springer
ISBN: 3030034992
Category : Science
Languages : en
Pages : 146
Book Description
This open access textbook provides the background needed to correctly use, interpret and understand statistics and statistical data in diverse settings. Part I makes key concepts in statistics readily clear. Parts I and II give an overview of the most common tests (t-test, ANOVA, correlations) and work out their statistical principles. Part III provides insight into meta-statistics (statistics of statistics) and demonstrates why experiments often do not replicate. Finally, the textbook shows how complex statistics can be avoided by using clever experimental design. Both non-scientists and students in Biology, Biomedicine and Engineering will benefit from the book by learning the statistical basis of scientific claims and by discovering ways to evaluate the quality of scientific reports in academic journals and news outlets.