Contributions To The Analysis Of Experiments Using Empirical Bayes Techniques

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Contributions to the Analysis of Experiments Using Empirical Bayes Techniques

Author : James Dillon Delaney
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (713 download)

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Book Synopsis Contributions to the Analysis of Experiments Using Empirical Bayes Techniques by : James Dillon Delaney

Download or read book Contributions to the Analysis of Experiments Using Empirical Bayes Techniques written by James Dillon Delaney and published by . This book was released on 2006 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Specifying a prior distribution for the large number of parameters in the linear statistical model is a difficult step in the Bayesian approach to the design and analysis of experiments. Here we address this difficulty by proposing the use of functional priors and then by working out important details for three and higher level experiments. One of the challenges presented by higher level experiments is that a factor can be either qualitative or quantitative. We propose appropriate correlation functions and coding schemes so that the prior distribution is simple and the results easily interpretable. The prior incorporates well known experimental design principles such as effect hierarchy and effect heredity, which helps to automatically resolve the aliasing problems experienced in fractional designs. The second part of the thesis focuses on the analysis of optimization experiments. Not uncommon are designed experiments with their primary purpose being to determine optimal settings for all of the factors in some predetermined set. Here we distinguish between the two concepts of statistical significance and practical significance. We perform estimation via an empirical Bayes data analysis methodology that has been detailed in the recent literature. But then propose an alternative to the usual next step in determining optimal factor level settings. Instead of implementing variable or model selection techniques, we propose an objective function that assists in our goal of finding the ideal settings for all factors over which we experimented. The usefulness of the new approach is illustrated through the analysis of some real experiments as well as simulation.

Some Contributions to Empirical Bayes Methods in Statistical Decision Theory

Author : Rohana Talagalage
Publisher :
ISBN 13 :
Total Pages : 202 pages
Book Rating : 4.:/5 (314 download)

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Book Synopsis Some Contributions to Empirical Bayes Methods in Statistical Decision Theory by : Rohana Talagalage

Download or read book Some Contributions to Empirical Bayes Methods in Statistical Decision Theory written by Rohana Talagalage and published by . This book was released on 1993 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Empirical Bayes Analysis of Some Sequential Experiments

Author : Glen Hortin Lemon
Publisher :
ISBN 13 :
Total Pages : 424 pages
Book Rating : 4.:/5 (41 download)

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Book Synopsis Empirical Bayes Analysis of Some Sequential Experiments by : Glen Hortin Lemon

Download or read book Empirical Bayes Analysis of Some Sequential Experiments written by Glen Hortin Lemon and published by . This book was released on 1968 with total page 424 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Probability and Bayesian Statistics

Author : R. Viertl
Publisher : Springer Science & Business Media
ISBN 13 : 1461318858
Total Pages : 505 pages
Book Rating : 4.4/5 (613 download)

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Book Synopsis Probability and Bayesian Statistics by : R. Viertl

Download or read book Probability and Bayesian Statistics written by R. Viertl and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 505 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains selected and refereed contributions to the "Inter national Symposium on Probability and Bayesian Statistics" which was orga nized to celebrate the 80th birthday of Professor Bruno de Finetti at his birthplace Innsbruck in Austria. Since Professor de Finetti died in 1985 the symposium was dedicated to the memory of Bruno de Finetti and took place at Igls near Innsbruck from 23 to 26 September 1986. Some of the pa pers are published especially by the relationship to Bruno de Finetti's scientific work. The evolution of stochastics shows growing importance of probability as coherent assessment of numerical values as degrees of believe in certain events. This is the basis for Bayesian inference in the sense of modern statistics. The contributions in this volume cover a broad spectrum ranging from foundations of probability across psychological aspects of formulating sub jective probability statements, abstract measure theoretical considerations, contributions to theoretical statistics and stochastic processes, to real applications in economics, reliability and hydrology. Also the question is raised if it is necessary to develop new techniques to model and analyze fuzzy observations in samples. The articles are arranged in alphabetical order according to the family name of the first author of each paper to avoid a hierarchical ordering of importance of the different topics. Readers interested in special topics can use the index at the end of the book as guide.

Doing Bayesian Data Analysis

Author : John Kruschke
Publisher : Academic Press
ISBN 13 : 0124059163
Total Pages : 776 pages
Book Rating : 4.1/5 (24 download)

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Book Synopsis Doing Bayesian Data Analysis by : John Kruschke

Download or read book Doing Bayesian Data Analysis written by John Kruschke and published by Academic Press. This book was released on 2014-11-11 with total page 776 pages. Available in PDF, EPUB and Kindle. Book excerpt: Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan, Second Edition provides an accessible approach for conducting Bayesian data analysis, as material is explained clearly with concrete examples. Included are step-by-step instructions on how to carry out Bayesian data analyses in the popular and free software R and WinBugs, as well as new programs in JAGS and Stan. The new programs are designed to be much easier to use than the scripts in the first edition. In particular, there are now compact high-level scripts that make it easy to run the programs on your own data sets. The book is divided into three parts and begins with the basics: models, probability, Bayes’ rule, and the R programming language. The discussion then moves to the fundamentals applied to inferring a binomial probability, before concluding with chapters on the generalized linear model. Topics include metric-predicted variable on one or two groups; metric-predicted variable with one metric predictor; metric-predicted variable with multiple metric predictors; metric-predicted variable with one nominal predictor; and metric-predicted variable with multiple nominal predictors. The exercises found in the text have explicit purposes and guidelines for accomplishment. This book is intended for first-year graduate students or advanced undergraduates in statistics, data analysis, psychology, cognitive science, social sciences, clinical sciences, and consumer sciences in business. Accessible, including the basics of essential concepts of probability and random sampling Examples with R programming language and JAGS software Comprehensive coverage of all scenarios addressed by non-Bayesian textbooks: t-tests, analysis of variance (ANOVA) and comparisons in ANOVA, multiple regression, and chi-square (contingency table analysis) Coverage of experiment planning R and JAGS computer programming code on website Exercises have explicit purposes and guidelines for accomplishment Provides step-by-step instructions on how to conduct Bayesian data analyses in the popular and free software R and WinBugs

Generalized Empirical Bayes

Author : Douglas Fletcher
Publisher :
ISBN 13 :
Total Pages : 159 pages
Book Rating : 4.:/5 (128 download)

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Book Synopsis Generalized Empirical Bayes by : Douglas Fletcher

Download or read book Generalized Empirical Bayes written by Douglas Fletcher and published by . This book was released on 2019 with total page 159 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two key issues of modern Bayesian statistics are: (i) establishing a principled approach for \textit{distilling} a statistical prior distribution that is \textit{consistent} with the given data from an initial believable scientific prior; and (ii) development of a \textit{consolidated} Bayes-frequentist data analysis workflow that is more effective than either of the two separately. In this thesis, we propose generalized empirical Bayes as a new framework for exploring these fundamental questions along with a wide range of applications spanning fields as diverse as clinical trials, metrology, insurance, medicine, and ecology. Our research marks a significant step towards bridging the ``gap'' between Bayesian and frequentist schools of thought that has plagued statisticians for over 250 years. Chapters 1 and 2--based on \cite{mukhopadhyay2018generalized}--introduces the core theory and methods of our proposed generalized empirical Bayes (gEB) framework that solves a long-standing puzzle of modern Bayes, originally posed by Herbert Robbins (1980). One of the main contributions of this research is to introduce and study a new class of nonparametric priors ${\rm DS}(G, m)$ that allows exploratory Bayesian modeling. However, at a practical level, major practical advantages of our proposal are: (i) computational ease (it does not require Markov chain Monte Carlo (MCMC), variational methods, or any other sophisticated computational techniques); (ii) simplicity and interpretability of the underlying theoretical framework which is general enough to include almost all commonly encountered models; and (iii) easy integration with mainframe Bayesian analysis that makes it readily applicable to a wide range of problems. Connections with other Bayesian cultures are also presented in the chapter. Chapter 3 deals with the topic of measurement uncertainty from a new angle by introducing the foundation of nonparametric meta-analysis. We have applied the proposed methodology to real data examples from astronomy, physics, and medical disciplines. Chapter 4 discusses some further extensions and application of our theory to distributed big data modeling and the missing species problem. The dissertation concludes by highlighting two important areas of future work: a full Bayesian implementation workflow and potential applications in cybersecurity.

Empirical Direction in Design and Analysis

Author : Norman H. Anderson
Publisher : Psychology Press
ISBN 13 : 1135643393
Total Pages : 879 pages
Book Rating : 4.1/5 (356 download)

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Book Synopsis Empirical Direction in Design and Analysis by : Norman H. Anderson

Download or read book Empirical Direction in Design and Analysis written by Norman H. Anderson and published by Psychology Press. This book was released on 2001-07-01 with total page 879 pages. Available in PDF, EPUB and Kindle. Book excerpt: The goal of Norman H. Anderson's new book is to help students develop skills of scientific inference. To accomplish this he organized the book around the "Experimental Pyramid"--six levels that represent a hierarchy of considerations in empirical investigation--conceptual framework, phenomena, behavior, measurement, design, and statistical inference. To facilitate conceptual and empirical understanding, Anderson de-emphasizes computational formulas and null hypothesis testing. Other features include: *emphasis on visual inspection as a basic skill in experimental analysis to help students develop an intuitive appreciation of data patterns; *exercises that emphasize development of conceptual and empirical application of methods of design and analysis and de-emphasize formulas and calculations; and *heavier emphasis on confidence intervals than significance tests. The book is intended for use in graduate-level experimental design/research methods or statistics courses in psychology, education, and other applied social sciences, as well as a professional resource for active researchers. The first 12 chapters present the core concepts graduate students must understand. The next nine chapters serve as a reference handbook by focusing on specialized topics with a minimum of technicalities.

Bayesian Data Analysis, Third Edition

Author : Andrew Gelman
Publisher : CRC Press
ISBN 13 : 1439840954
Total Pages : 677 pages
Book Rating : 4.4/5 (398 download)

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Book Synopsis Bayesian Data Analysis, Third Edition by : Andrew Gelman

Download or read book Bayesian Data Analysis, Third Edition written by Andrew Gelman and published by CRC Press. This book was released on 2013-11-01 with total page 677 pages. Available in PDF, EPUB and Kindle. Book excerpt: Now in its third edition, this classic book is widely considered the leading text on Bayesian methods, lauded for its accessible, practical approach to analyzing data and solving research problems. Bayesian Data Analysis, Third Edition continues to take an applied approach to analysis using up-to-date Bayesian methods. The authors—all leaders in the statistics community—introduce basic concepts from a data-analytic perspective before presenting advanced methods. Throughout the text, numerous worked examples drawn from real applications and research emphasize the use of Bayesian inference in practice. New to the Third Edition Four new chapters on nonparametric modeling Coverage of weakly informative priors and boundary-avoiding priors Updated discussion of cross-validation and predictive information criteria Improved convergence monitoring and effective sample size calculations for iterative simulation Presentations of Hamiltonian Monte Carlo, variational Bayes, and expectation propagation New and revised software code The book can be used in three different ways. For undergraduate students, it introduces Bayesian inference starting from first principles. For graduate students, the text presents effective current approaches to Bayesian modeling and computation in statistics and related fields. For researchers, it provides an assortment of Bayesian methods in applied statistics. Additional materials, including data sets used in the examples, solutions to selected exercises, and software instructions, are available on the book’s web page.

Empirical Bayes Methods with Applications

Author : J.S. Maritz
Publisher : CRC Press
ISBN 13 : 1351080113
Total Pages : 296 pages
Book Rating : 4.3/5 (51 download)

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Book Synopsis Empirical Bayes Methods with Applications by : J.S. Maritz

Download or read book Empirical Bayes Methods with Applications written by J.S. Maritz and published by CRC Press. This book was released on 2018-01-18 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: The second edition of Empirical Bayes Methods details are provided of the derivation and the performance of empirical Bayes rules for a variety of special models. Attention is given to the problem of assessing the goodness of an empirical Bayes estimator for a given set of prior data. A chapter is devoted to a discussion of alternatives to the empirical Bayes approach and there is also a chapter giving details of several actual applications of empirical Bayes method.

The Subjectivity of Scientists and the Bayesian Approach

Author : S. James Press
Publisher : John Wiley & Sons
ISBN 13 : 1118150627
Total Pages : 296 pages
Book Rating : 4.1/5 (181 download)

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Book Synopsis The Subjectivity of Scientists and the Bayesian Approach by : S. James Press

Download or read book The Subjectivity of Scientists and the Bayesian Approach written by S. James Press and published by John Wiley & Sons. This book was released on 2012-01-20 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: Comparing and contrasting the reality of subjectivity in the workof history's great scientists and the modern Bayesian approach tostatistical analysis Scientists and researchers are taught to analyze their data from anobjective point of view, allowing the data to speak for themselvesrather than assigning them meaning based on expectations oropinions. But scientists have never behaved fully objectively.Throughout history, some of our greatest scientific minds haverelied on intuition, hunches, and personal beliefs to make sense ofempirical data-and these subjective influences have often aided inhumanity's greatest scientific achievements. The authors argue thatsubjectivity has not only played a significant role in theadvancement of science, but that science will advance more rapidlyif the modern methods of Bayesian statistical analysis replace someof the classical twentieth-century methods that have traditionallybeen taught. To accomplish this goal, the authors examine the lives and work ofhistory's great scientists and show that even the most successfulhave sometimes misrepresented findings or been influenced by theirown preconceived notions of religion, metaphysics, and the occult,or the personal beliefs of their mentors. Contrary to popularbelief, our greatest scientific thinkers approached their data witha combination of subjectivity and empiricism, and thus informallyachieved what is more formally accomplished by the modern Bayesianapproach to data analysis. Yet we are still taught that science is purely objective. Thisinnovative book dispels that myth using historical accounts andbiographical sketches of more than a dozen great scientists,including Aristotle, Galileo Galilei, Johannes Kepler, WilliamHarvey, Sir Isaac Newton, Antoine Levoisier, Alexander vonHumboldt, Michael Faraday, Charles Darwin, Louis Pasteur, GregorMendel, Sigmund Freud, Marie Curie, Robert Millikan, AlbertEinstein, Sir Cyril Burt, and Margaret Mead. Also included is adetailed treatment of the modern Bayesian approach to dataanalysis. Up-to-date references to the Bayesian theoretical andapplied literature, as well as reference lists of the primarysources of the principal works of all the scientists discussed,round out this comprehensive treatment of the subject. Readers will benefit from this cogent and enlightening view of thehistory of subjectivity in science and the authors' alternativevision of how the Bayesian approach should be used to further thecause of science and learning well into the twenty-first century.

Adaptive Experimentation for Hypothesis Testing in the Empirical Bayes Situation

Author : Richard James Brand
Publisher :
ISBN 13 :
Total Pages : 172 pages
Book Rating : 4.:/5 (29 download)

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Book Synopsis Adaptive Experimentation for Hypothesis Testing in the Empirical Bayes Situation by : Richard James Brand

Download or read book Adaptive Experimentation for Hypothesis Testing in the Empirical Bayes Situation written by Richard James Brand and published by . This book was released on 1969 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Empirical Bayes Methods

Author : J. S. Maritz
Publisher : Routledge
ISBN 13 : 1351140639
Total Pages : 299 pages
Book Rating : 4.3/5 (511 download)

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Book Synopsis Empirical Bayes Methods by : J. S. Maritz

Download or read book Empirical Bayes Methods written by J. S. Maritz and published by Routledge. This book was released on 2018-03-05 with total page 299 pages. Available in PDF, EPUB and Kindle. Book excerpt: Originally published in 1970; with a second edition in 1989. Empirical Bayes methods use some of the apparatus of the pure Bayes approach, but an actual prior distribution is assumed to generate the data sequence. It can be estimated thus producing empirical Bayes estimates or decision rules. In this second edition, details are provided of the derivation and the performance of empirical Bayes rules for a variety of special models. Attention is given to the problem of assessing the goodness of an empirical Bayes estimator for a given set of prior data. Chapters also focus on alternatives to the empirical Bayes approach and actual applications of empirical Bayes methods.

Bayes and Empirical Bayes Methods for Combining Cancer Experiments in Man and Other Species

Author : William H. DuMouchel
Publisher :
ISBN 13 :
Total Pages : 52 pages
Book Rating : 4.:/5 (959 download)

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Book Synopsis Bayes and Empirical Bayes Methods for Combining Cancer Experiments in Man and Other Species by : William H. DuMouchel

Download or read book Bayes and Empirical Bayes Methods for Combining Cancer Experiments in Man and Other Species written by William H. DuMouchel and published by . This book was released on 1981 with total page 52 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Methods of Meta-Analysis

Author : John E Hunter
Publisher : SAGE
ISBN 13 : 1412909120
Total Pages : 616 pages
Book Rating : 4.4/5 (129 download)

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Book Synopsis Methods of Meta-Analysis by : John E Hunter

Download or read book Methods of Meta-Analysis written by John E Hunter and published by SAGE. This book was released on 2004-04-19 with total page 616 pages. Available in PDF, EPUB and Kindle. Book excerpt: Covering the most important developments in meta-analysis from 1990 to 2004, this text presents new patterns in research findings as well as updated information on existing topics.

Bayesian Analysis in Statistics and Econometrics

Author : Prem K. Goel
Publisher : Springer Science & Business Media
ISBN 13 : 1461229448
Total Pages : 409 pages
Book Rating : 4.4/5 (612 download)

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Book Synopsis Bayesian Analysis in Statistics and Econometrics by : Prem K. Goel

Download or read book Bayesian Analysis in Statistics and Econometrics written by Prem K. Goel and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 409 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume is based on the invited and the contributed presentations given at the Indo-U.S. Workshop on Bayesian Analysis in Statistics and Econometrics (BASE), Dec. 19-23, 1988, held at the Hotel Taj Residency, Bangalore, India. The workshop was jointly sponsored by The Ohio State University, The Indian Statistical Institute, The Indian Econometrics So ciety, U.S. National Science Foundation and the NSF-NBER Seminar on Bayesian Inference in Econometrics. Profs. Morrie DeGroot, Prem Goel, and Arnold Zellner were the program organizers. Unfortunately, Morrie became seriously ill just before the workshop was to start and could not participate in the workshop. Almost a year later, Morrie passed away after fighting valiantly with the illness. Not to find Morrie among ourselves was a shock for most of us. He was a continuous source of inspiration and ideas. Even while Morrie was fighting for his life, we had a lot of discussions about the contents of this volume and the Bangalore Workshop. He even talked about organizing a Second Indo-U.S. workshop some time in the near future. We are dedicating this volume to the memory of Prof. Morris H. DeGroot. We have taken a conscious decision not to include any biography of Morrie in this volume. An excellent biography of Morrie has appeared in Statistical Science [(1991), vol. 6, 1-14], and we could not have done a better job than that.

Journal of the National Cancer Institute

Author :
Publisher :
ISBN 13 :
Total Pages : 720 pages
Book Rating : 4.:/5 (334 download)

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Book Synopsis Journal of the National Cancer Institute by :

Download or read book Journal of the National Cancer Institute written by and published by . This book was released on 2004 with total page 720 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Batch Effects and Noise in Microarray Experiments

Author : Andreas Scherer
Publisher : John Wiley & Sons
ISBN 13 : 0470741384
Total Pages : 292 pages
Book Rating : 4.4/5 (77 download)

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Book Synopsis Batch Effects and Noise in Microarray Experiments by : Andreas Scherer

Download or read book Batch Effects and Noise in Microarray Experiments written by Andreas Scherer and published by John Wiley & Sons. This book was released on 2009-12-14 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: Batch Effects and Noise in Microarray Experiments: Sources and Solutions looks at the issue of technical noise and batch effects in microarray studies and illustrates how to alleviate such factors whilst interpreting the relevant biological information. Each chapter focuses on sources of noise and batch effects before starting an experiment, with examples of statistical methods for detecting, measuring, and managing batch effects within and across datasets provided online. Throughout the book the importance of standardization and the value of standard operating procedures in the development of genomics biomarkers is emphasized. Key Features: A thorough introduction to Batch Effects and Noise in Microrarray Experiments. A unique compilation of review and research articles on handling of batch effects and technical and biological noise in microarray data. An extensive overview of current standardization initiatives. All datasets and methods used in the chapters, as well as colour images, are available on www.the-batch-effect-book.org, so that the data can be reproduced. An exciting compilation of state-of-the-art review chapters and latest research results, which will benefit all those involved in the planning, execution, and analysis of gene expression studies.