Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
Numerical Approaches For Sequential Bayesian Optimal Experimental Design
Download Numerical Approaches For Sequential Bayesian Optimal Experimental Design full books in PDF, epub, and Kindle. Read online Numerical Approaches For Sequential Bayesian Optimal Experimental Design ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Book Synopsis Sequential Analysis and Optimal Design by : Herman Chernoff
Download or read book Sequential Analysis and Optimal Design written by Herman Chernoff and published by SIAM. This book was released on 1972-01-01 with total page 124 pages. Available in PDF, EPUB and Kindle. Book excerpt: An exploration of the interrelated fields of design of experiments and sequential analysis with emphasis on the nature of theoretical statistics and how this relates to the philosophy and practice of statistics.
Book Synopsis Functional Approach to Optimal Experimental Design by : Viatcheslav B. Melas
Download or read book Functional Approach to Optimal Experimental Design written by Viatcheslav B. Melas and published by Springer Science & Business Media. This book was released on 2006-04-20 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: The present book is devoted to studying optimal experimental designs for a wide class of linear and nonlinear regression models. This class includes polynomial, trigonometrical, rational, and exponential models as well as many particular models used in ecology and microbiology. As the criteria of optimality, the well known D-, E-, and c-criteria are implemented. The main idea of the book is to study the dependence of optimal - signs on values of unknown parameters and on the bounds of the design interval. Such a study can be performed on the base of the Implicit Fu- tion Theorem, the classical result of functional analysis. The idea was ?rst introduced in the author’s paper (Melas, 1978) for nonlinear in parameters exponential models. Recently, it was developed for other models in a n- ber of works (Melas (1995, 2000, 2001, 2004, 2005), Dette, Melas (2002, 2003), Dette, Melas, Pepelyshev (2002, 2003, 2004b), and Dette, Melas, Biederman (2002)). Thepurposeofthepresentbookistobringtogethertheresultsobtained and to develop further underlying concepts and tools. The approach, m- tioned above, will be called the functional approach. Its brief description can be found in the Introduction. The book contains eight chapters. The ?rst chapter introduces basic concepts and results of optimal design theory, initiated mainly by J.Kiefer.
Book Synopsis Sequential Monte Carlo Methods in Practice by : Arnaud Doucet
Download or read book Sequential Monte Carlo Methods in Practice written by Arnaud Doucet and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 590 pages. Available in PDF, EPUB and Kindle. Book excerpt: Monte Carlo methods are revolutionizing the on-line analysis of data in many fileds. They have made it possible to solve numerically many complex, non-standard problems that were previously intractable. This book presents the first comprehensive treatment of these techniques.
Book Synopsis Theory Of Optimal Experiments by : V.V. Fedorov
Download or read book Theory Of Optimal Experiments written by V.V. Fedorov and published by Elsevier. This book was released on 2013-04-20 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: Theory Of Optimal Experiments
Book Synopsis The Design and Analysis of Computer Experiments by : Thomas J. Santner
Download or read book The Design and Analysis of Computer Experiments written by Thomas J. Santner and published by Springer. This book was released on 2019-01-08 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes methods for designing and analyzing experiments that are conducted using a computer code, a computer experiment, and, when possible, a physical experiment. Computer experiments continue to increase in popularity as surrogates for and adjuncts to physical experiments. Since the publication of the first edition, there have been many methodological advances and software developments to implement these new methodologies. The computer experiments literature has emphasized the construction of algorithms for various data analysis tasks (design construction, prediction, sensitivity analysis, calibration among others), and the development of web-based repositories of designs for immediate application. While it is written at a level that is accessible to readers with Masters-level training in Statistics, the book is written in sufficient detail to be useful for practitioners and researchers. New to this revised and expanded edition: • An expanded presentation of basic material on computer experiments and Gaussian processes with additional simulations and examples • A new comparison of plug-in prediction methodologies for real-valued simulator output • An enlarged discussion of space-filling designs including Latin Hypercube designs (LHDs), near-orthogonal designs, and nonrectangular regions • A chapter length description of process-based designs for optimization, to improve good overall fit, quantile estimation, and Pareto optimization • A new chapter describing graphical and numerical sensitivity analysis tools • Substantial new material on calibration-based prediction and inference for calibration parameters • Lists of software that can be used to fit models discussed in the book to aid practitioners
Book Synopsis Sequential Experimentation in Clinical Trials by : Jay Bartroff
Download or read book Sequential Experimentation in Clinical Trials written by Jay Bartroff and published by Springer Science & Business Media. This book was released on 2012-12-12 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sequential Experimentation in Clinical Trials: Design and Analysis is developed from decades of work in research groups, statistical pedagogy, and workshop participation. Different parts of the book can be used for short courses on clinical trials, translational medical research, and sequential experimentation. The authors have successfully used the book to teach innovative clinical trial designs and statistical methods for Statistics Ph.D. students at Stanford University. There are additional online supplements for the book that include chapter-specific exercises and information. Sequential Experimentation in Clinical Trials: Design and Analysis covers the much broader subject of sequential experimentation that includes group sequential and adaptive designs of Phase II and III clinical trials, which have attracted much attention in the past three decades. In particular, the broad scope of design and analysis problems in sequential experimentation clearly requires a wide range of statistical methods and models from nonlinear regression analysis, experimental design, dynamic programming, survival analysis, resampling, and likelihood and Bayesian inference. The background material in these building blocks is summarized in Chapter 2 and Chapter 3 and certain sections in Chapter 6 and Chapter 7. Besides group sequential tests and adaptive designs, the book also introduces sequential change-point detection methods in Chapter 5 in connection with pharmacovigilance and public health surveillance. Together with dynamic programming and approximate dynamic programming in Chapter 3, the book therefore covers all basic topics for a graduate course in sequential analysis designs.
Book Synopsis Optimal Design of Experiments by : Friedrich Pukelsheim
Download or read book Optimal Design of Experiments written by Friedrich Pukelsheim and published by SIAM. This book was released on 2006-04-01 with total page 527 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimal Design of Experiments offers a rare blend of linear algebra, convex analysis, and statistics. The optimal design for statistical experiments is first formulated as a concave matrix optimization problem. Using tools from convex analysis, the problem is solved generally for a wide class of optimality criteria such as D-, A-, or E-optimality. The book then offers a complementary approach that calls for the study of the symmetry properties of the design problem, exploiting such notions as matrix majorization and the Kiefer matrix ordering. The results are illustrated with optimal designs for polynomial fit models, Bayes designs, balanced incomplete block designs, exchangeable designs on the cube, rotatable designs on the sphere, and many other examples.
Book Synopsis Optimal Design of Experiments by : Peter Goos
Download or read book Optimal Design of Experiments written by Peter Goos and published by John Wiley & Sons. This book was released on 2011-06-28 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This is an engaging and informative book on the modern practice of experimental design. The authors' writing style is entertaining, the consulting dialogs are extremely enjoyable, and the technical material is presented brilliantly but not overwhelmingly. The book is a joy to read. Everyone who practices or teaches DOE should read this book." - Douglas C. Montgomery, Regents Professor, Department of Industrial Engineering, Arizona State University "It's been said: 'Design for the experiment, don't experiment for the design.' This book ably demonstrates this notion by showing how tailor-made, optimal designs can be effectively employed to meet a client's actual needs. It should be required reading for anyone interested in using the design of experiments in industrial settings." —Christopher J. Nachtsheim, Frank A Donaldson Chair in Operations Management, Carlson School of Management, University of Minnesota This book demonstrates the utility of the computer-aided optimal design approach using real industrial examples. These examples address questions such as the following: How can I do screening inexpensively if I have dozens of factors to investigate? What can I do if I have day-to-day variability and I can only perform 3 runs a day? How can I do RSM cost effectively if I have categorical factors? How can I design and analyze experiments when there is a factor that can only be changed a few times over the study? How can I include both ingredients in a mixture and processing factors in the same study? How can I design an experiment if there are many factor combinations that are impossible to run? How can I make sure that a time trend due to warming up of equipment does not affect the conclusions from a study? How can I take into account batch information in when designing experiments involving multiple batches? How can I add runs to a botched experiment to resolve ambiguities? While answering these questions the book also shows how to evaluate and compare designs. This allows researchers to make sensible trade-offs between the cost of experimentation and the amount of information they obtain.
Book Synopsis Bayesian Filtering and Smoothing by : Simo Särkkä
Download or read book Bayesian Filtering and Smoothing written by Simo Särkkä and published by Cambridge University Press. This book was released on 2013-09-05 with total page 255 pages. Available in PDF, EPUB and Kindle. Book excerpt: A unified Bayesian treatment of the state-of-the-art filtering, smoothing, and parameter estimation algorithms for non-linear state space models.
Book Synopsis Optimal Experimental Design with R by : Dieter Rasch
Download or read book Optimal Experimental Design with R written by Dieter Rasch and published by CRC Press. This book was released on 2011-05-18 with total page 345 pages. Available in PDF, EPUB and Kindle. Book excerpt: Experimental design is often overlooked in the literature of applied and mathematical statistics: statistics is taught and understood as merely a collection of methods for analyzing data. Consequently, experimenters seldom think about optimal design, including prerequisites such as the necessary sample size needed for a precise answer for an experi
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.
Book Synopsis Sequential Analysis by : Abraham Wald
Download or read book Sequential Analysis written by Abraham Wald and published by Courier Corporation. This book was released on 2013-11-26 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first to solve the general problem of sequential tests of statistical hypotheses, the author of this text explains his revolutionary theory of the sequential probability ratio test and its applications. 1947 edition.
Book Synopsis Statistical Methods for Reliability Data by : William Q. Meeker
Download or read book Statistical Methods for Reliability Data written by William Q. Meeker and published by John Wiley & Sons. This book was released on 2022-01-24 with total page 708 pages. Available in PDF, EPUB and Kindle. Book excerpt: An authoritative guide to the most recent advances in statistical methods for quantifying reliability Statistical Methods for Reliability Data, Second Edition (SMRD2) is an essential guide to the most widely used and recently developed statistical methods for reliability data analysis and reliability test planning. Written by three experts in the area, SMRD2 updates and extends the long- established statistical techniques and shows how to apply powerful graphical, numerical, and simulation-based methods to a range of applications in reliability. SMRD2 is a comprehensive resource that describes maximum likelihood and Bayesian methods for solving practical problems that arise in product reliability and similar areas of application. SMRD2 illustrates methods with numerous applications and all the data sets are available on the book’s website. Also, SMRD2 contains an extensive collection of exercises that will enhance its use as a course textbook. The SMRD2's website contains valuable resources, including R packages, Stan model codes, presentation slides, technical notes, information about commercial software for reliability data analysis, and csv files for the 93 data sets used in the book's examples and exercises. The importance of statistical methods in the area of engineering reliability continues to grow and SMRD2 offers an updated guide for, exploring, modeling, and drawing conclusions from reliability data. SMRD2 features: Contains a wealth of information on modern methods and techniques for reliability data analysis Offers discussions on the practical problem-solving power of various Bayesian inference methods Provides examples of Bayesian data analysis performed using the R interface to the Stan system based on Stan models that are available on the book's website Includes helpful technical-problem and data-analysis exercise sets at the end of every chapter Presents illustrative computer graphics that highlight data, results of analyses, and technical concepts Written for engineers and statisticians in industry and academia, Statistical Methods for Reliability Data, Second Edition offers an authoritative guide to this important topic.
Book Synopsis A First Course in the Numerical Analysis of Differential Equations by : A. Iserles
Download or read book A First Course in the Numerical Analysis of Differential Equations written by A. Iserles and published by Cambridge University Press. This book was released on 2009 with total page 481 pages. Available in PDF, EPUB and Kindle. Book excerpt: lead the reader to a theoretical understanding of the subject without neglecting its practical aspects. The outcome is a textbook that is mathematically honest and rigorous and provides its target audience with a wide range of skills in both ordinary and partial differential equations." --Book Jacket.
Book Synopsis From Sounds to Music and Emotions by : Mitsuko Aramaki
Download or read book From Sounds to Music and Emotions written by Mitsuko Aramaki and published by Springer. This book was released on 2013-09-12 with total page 514 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-conference proceedings of the 9th International Symposium on Computer Music Modeling and Retrieval, CMMR 2012, held in London, UK, in June 2012. The 28 revised full papers presented were carefully reviewed and selected for inclusion in this volume. The papers have been organized in the following topical sections: music emotion analysis; 3D audio and sound synthesis; computer models of music perception and cognition; music emotion recognition; music information retrieval; film soundtrack and music recommendation; and computational musicology and music education. The volume also includes selected papers from the Cross-Disciplinary Perspectives on Expressive Performance Workshop held within the framework of CMMR 2012.
Book Synopsis A Course in Reinforcement Learning by : Dimitri Bertsekas
Download or read book A Course in Reinforcement Learning written by Dimitri Bertsekas and published by Athena Scientific. This book was released on 2023-06-21 with total page 421 pages. Available in PDF, EPUB and Kindle. Book excerpt: These lecture notes were prepared for use in the 2023 ASU research-oriented course on Reinforcement Learning (RL) that I have offered in each of the last five years. Their purpose is to give an overview of the RL methodology, particularly as it relates to problems of optimal and suboptimal decision and control, as well as discrete optimization. There are two major methodological RL approaches: approximation in value space, where we approximate in some way the optimal value function, and approximation in policy space, whereby we construct a (generally suboptimal) policy by using optimization over a suitably restricted class of policies.The lecture notes focus primarily on approximation in value space, with limited coverage of approximation in policy space. However, they are structured so that they can be easily supplemented by an instructor who wishes to go into approximation in policy space in greater detail, using any of a number of available sources, including the author's 2019 RL book. While in these notes we deemphasize mathematical proofs, there is considerable related analysis, which supports our conclusions and can be found in the author's recent RL and DP books. These books also contain additional material on off-line training of neural networks, on the use of policy gradient methods for approximation in policy space, and on aggregation.
Book Synopsis Handbook of Design and Analysis of Experiments by : Angela Dean
Download or read book Handbook of Design and Analysis of Experiments written by Angela Dean and published by CRC Press. This book was released on 2015-06-26 with total page 946 pages. Available in PDF, EPUB and Kindle. Book excerpt: This carefully edited collection synthesizes the state of the art in the theory and applications of designed experiments and their analyses. It provides a detailed overview of the tools required for the optimal design of experiments and their analyses. The handbook covers many recent advances in the field, including designs for nonlinear models and algorithms applicable to a wide variety of design problems. It also explores the extensive use of experimental designs in marketing, the pharmaceutical industry, engineering and other areas.
