Download or read book A Mixture Model Approach to Empirical Bayes Testing and Estimation written by Omkar Muralidharan and published by Stanford University. This book was released on 2011 with total page 89 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many modern statistical problems require making similar decisions or estimates for many different entities. For example, we may ask whether each of 10,000 genes is associated with some disease, or try to measure the degree to which each is associated with the disease. As in this example, the entities can often be divided into a vast majority of "null" objects and a small minority of interesting ones. Empirical Bayes is a useful technique for such situations, but finding the right empirical Bayes method for each problem can be difficult. Mixture models, however, provide an easy and effective way to apply empirical Bayes. This thesis motivates mixture models by analyzing a simple high-dimensional problem, and shows their practical use by applying them to detecting single nucleotide polymorphisms.
Download or read book Finite Mixture Models written by Geoffrey McLachlan and published by John Wiley & Sons. This book was released on 2004-03-22 with total page 419 pages. Available in PDF, EPUB and Kindle. Book excerpt: An up-to-date, comprehensive account of major issues in finitemixture modeling This volume provides an up-to-date account of the theory andapplications of modeling via finite mixture distributions. With anemphasis on the applications of mixture models in both mainstreamanalysis and other areas such as unsupervised pattern recognition,speech recognition, and medical imaging, the book describes theformulations of the finite mixture approach, details itsmethodology, discusses aspects of its implementation, andillustrates its application in many common statisticalcontexts. Major issues discussed in this book include identifiabilityproblems, actual fitting of finite mixtures through use of the EMalgorithm, properties of the maximum likelihood estimators soobtained, assessment of the number of components to be used in themixture, and the applicability of asymptotic theory in providing abasis for the solutions to some of these problems. The author alsoconsiders how the EM algorithm can be scaled to handle the fittingof mixture models to very large databases, as in data miningapplications. This comprehensive, practical guide: * Provides more than 800 references-40% published since 1995 * Includes an appendix listing available mixture software * Links statistical literature with machine learning and patternrecognition literature * Contains more than 100 helpful graphs, charts, and tables Finite Mixture Models is an important resource for both applied andtheoretical statisticians as well as for researchers in the manyareas in which finite mixture models can be used to analyze data.
Download or read book Nonlinear Mixture Models A Bayesian Approach written by Tatiana V Tatarinova and published by World Scientific. This book was released on 2014-12-30 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book, written by two mathematicians from the University of Southern California, provides a broad introduction to the important subject of nonlinear mixture models from a Bayesian perspective. It contains background material, a brief description of Markov chain theory, as well as novel algorithms and their applications. It is self-contained and unified in presentation, which makes it ideal for use as an advanced textbook by graduate students and as a reference for independent researchers. The explanations in the book are detailed enough to capture the interest of the curious reader, and complete enough to provide the necessary background material needed to go further into the subject and explore the research literature.In this book the authors present Bayesian methods of analysis for nonlinear, hierarchical mixture models, with a finite, but possibly unknown, number of components. These methods are then applied to various problems including population pharmacokinetics and gene expression analysis. In population pharmacokinetics, the nonlinear mixture model, based on previous clinical data, becomes the prior distribution for individual therapy. For gene expression data, one application included in the book is to determine which genes should be associated with the same component of the mixture (also known as a clustering problem). The book also contains examples of computer programs written in BUGS. This is the first book of its kind to cover many of the topics in this field.
Download or read book Proceedings of the International Symposium on Computer Mapping in Epidemiology and Environmental Health written by and published by . This book was released on 1997 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book The Bayesian Choice written by Christian P. Robert and published by Springer Science & Business Media. This book was released on 2013-04-17 with total page 444 pages. Available in PDF, EPUB and Kindle. Book excerpt: This graduate-level textbook covers both the basic ideas of statistical theory, and also some of the more modern and advanced topics of Bayesian statistics, such as complete class theorems, the Stein effect, hierarchical and empirical Bayes modelling, Monte Carlo integration, and Gibbs sampling. In translating the book from the original French, the author has taken the opportunity to add and update material, and to include many problems and exercises for students.
Download or read book Design and Analysis of Clinical Trials for Predictive Medicine written by Shigeyuki Matsui and published by CRC Press. This book was released on 2015-03-19 with total page 394 pages. Available in PDF, EPUB and Kindle. Book excerpt: Design and Analysis of Clinical Trials for Predictive Medicine provides statistical guidance on conducting clinical trials for predictive medicine. It covers statistical topics relevant to the main clinical research phases for developing molecular diagnostics and therapeutics-from identifying molecular biomarkers using DNA microarrays to confirming
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.
Download or read book DNA Microarrays and Related Genomics Techniques written by David B. Allison and published by CRC Press. This book was released on 2005-11-14 with total page 391 pages. Available in PDF, EPUB and Kindle. Book excerpt: Considered highly exotic tools as recently as the late 1990s, microarrays are now ubiquitous in biological research. Traditional statistical approaches to design and analysis were not developed to handle the high-dimensional, small sample problems posed by microarrays. In just a few short years the number of statistical papers providing approaches
Download or read book Data Gathering Analysis and Protection of Privacy Through Randomized Response Techniques Qualitative and Quantitative Human Traits written by and published by Elsevier. This book was released on 2016-04-20 with total page 545 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Gathering, Analysis and Protection of Privacy through Randomized Response Techniques: Qualitative and Quantitative Human Traits tackles how to gather and analyze data relating to stigmatizing human traits. S.L. Warner invented RRT and published it in JASA, 1965. In the 50 years since, the subject has grown tremendously, with continued growth. This book comprehensively consolidates the literature to commemorate the inception of RR. - Brings together all relevant aspects of randomized response and indirect questioning - Tackles how to gather and analyze data relating to stigmatizing human traits - Gives an encyclopedic coverage of the topic - Covers recent developments and extrapolates to future trends
Download or read book Bayesian Modeling in Bioinformatics written by Dipak K. Dey and published by CRC Press. This book was released on 2010-09-03 with total page 466 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian Modeling in Bioinformatics discusses the development and application of Bayesian statistical methods for the analysis of high-throughput bioinformatics data arising from problems in molecular and structural biology and disease-related medical research, such as cancer. It presents a broad overview of statistical inference, clustering, and c
Download or read book Optimality written by Javier Rojo and published by IMS. This book was released on 2006 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt: The volume presents a collection of refereed papers dealing with the issue of optimality in several areas including: multiple testing, transformation models, competing risks, regression trees, density estimation, copulas, and robustness.
Download or read book Phenotypes and Genotypes written by Florian Frommlet and published by Springer. This book was released on 2016-02-12 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: This timely text presents a comprehensive guide to genetic association, a new and rapidly expanding field that aims to elucidate how our genetic code (genotypes) influences the traits we possess (phenotypes). The book provides a detailed review of methods of gene mapping used in association with experimental crosses, as well as genome-wide association studies. Emphasis is placed on model selection procedures for analyzing data from large-scale genome scans based on specifically designed modifications of the Bayesian information criterion. Features: presents a thorough introduction to the theoretical background to studies of genetic association (both genetic and statistical); reviews the latest advances in the field; illustrates the properties of methods for mapping quantitative trait loci using computer simulations and the analysis of real data; discusses open challenges; includes an extensive statistical appendix as a reference for those who are not totally familiar with the fundamentals of statistics.
Download or read book Mixture Models written by Bruce G. Lindsay and published by IMS. This book was released on 1995 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Handbook of Big Data Analytics written by Wolfgang Karl Härdle and published by Springer. This book was released on 2018-07-20 with total page 532 pages. Available in PDF, EPUB and Kindle. Book excerpt: Addressing a broad range of big data analytics in cross-disciplinary applications, this essential handbook focuses on the statistical prospects offered by recent developments in this field. To do so, it covers statistical methods for high-dimensional problems, algorithmic designs, computation tools, analysis flows and the software-hardware co-designs that are needed to support insightful discoveries from big data. The book is primarily intended for statisticians, computer experts, engineers and application developers interested in using big data analytics with statistics. Readers should have a solid background in statistics and computer science.
Download or read book Large Scale Inference written by Bradley Efron and published by Cambridge University Press. This book was released on 2012-11-29 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: We live in a new age for statistical inference, where modern scientific technology such as microarrays and fMRI machines routinely produce thousands and sometimes millions of parallel data sets, each with its own estimation or testing problem. Doing thousands of problems at once is more than repeated application of classical methods. Taking an empirical Bayes approach, Bradley Efron, inventor of the bootstrap, shows how information accrues across problems in a way that combines Bayesian and frequentist ideas. Estimation, testing and prediction blend in this framework, producing opportunities for new methodologies of increased power. New difficulties also arise, easily leading to flawed inferences. This book takes a careful look at both the promise and pitfalls of large-scale statistical inference, with particular attention to false discovery rates, the most successful of the new statistical techniques. Emphasis is on the inferential ideas underlying technical developments, illustrated using a large number of real examples.
Download or read book Analyzing Microarray Gene Expression Data written by Geoffrey J. McLachlan and published by John Wiley & Sons. This book was released on 2005-02-18 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt: A multi-discipline, hands-on guide to microarray analysis of biological processes Analyzing Microarray Gene Expression Data provides a comprehensive review of available methodologies for the analysis of data derived from the latest DNA microarray technologies. Designed for biostatisticians entering the field of microarray analysis as well as biologists seeking to more effectively analyze their own experimental data, the text features a unique interdisciplinary approach and a combined academic and practical perspective that offers readers the most complete and applied coverage of the subject matter to date. Following a basic overview of the biological and technical principles behind microarray experimentation, the text provides a look at some of the most effective tools and procedures for achieving optimum reliability and reproducibility of research results, including: An in-depth account of the detection of genes that are differentially expressed across a number of classes of tissues Extensive coverage of both cluster analysis and discriminant analysis of microarray data and the growing applications of both methodologies A model-based approach to cluster analysis, with emphasis on the use of the EMMIX-GENE procedure for the clustering of tissue samples The latest data cleaning and normalization procedures The uses of microarray expression data for providing important prognostic information on the outcome of disease
Download or read book Medical Product Safety Evaluation written by Jie Chen and published by CRC Press. This book was released on 2018-09-03 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: Medical Product Safety Evaluation: Biological Models and Statistical Methods presents cutting-edge biological models and statistical methods that are tailored to specific objectives and data types for safety analysis and benefit-risk assessment. Some frequently encountered issues and challenges in the design and analysis of safety studies are discussed with illustrative applications and examples. Medical Product Safety Evaluation: Biological Models and Statistical Methods presents cutting-edge biological models and statistical methods that are tailored to specific objectives and data types for safety analysis and benefit-risk assessment. Some frequently encountered issues and challenges in the design and analysis of safety studies are discussed with illustrative applications and examples. The book is designed not only for biopharmaceutical professionals, such as statisticians, safety specialists, pharmacovigilance experts, and pharmacoepidemiologists, who can use the book as self-learning materials or in short courses or training programs, but also for graduate students in statistics and biomedical data science for a one-semester course. Each chapter provides supplements and problems as more readings and exercises.
