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Optimal Statistical Decisions
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Book Synopsis Optimal Statistical Decisions by : Morris H. DeGroot
Download or read book Optimal Statistical Decisions written by Morris H. DeGroot and published by John Wiley & Sons. This book was released on 2005-01-28 with total page 511 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Wiley Classics Library consists of selected books that have become recognized classics in their respective fields. With these new unabridged and inexpensive editions, Wiley hopes to extend the life of these important works by making them available to future generations of mathematicians and scientists.
Download or read book Optimal Statistical Decisions written by and published by . This book was released on 2005 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The Wiley Classics Library consists of selected books that have become recognized classics in their respective fields. With these new unabridged and inexpensive editions, Wiley hopes to extend the life of these important works by making them available to future generations of mathematicians and scientists.
Book Synopsis Optimal Statistical Decisions by : Morris H. Degroot
Download or read book Optimal Statistical Decisions written by Morris H. Degroot and published by . This book was released on 1993 with total page 489 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Optimal Decision Making in Operations Research and Statistics by : Irfan Ali
Download or read book Optimal Decision Making in Operations Research and Statistics written by Irfan Ali and published by CRC Press. This book was released on 2021-11-29 with total page 434 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book provides insights in the decision-making for implementing strategies in various spheres of real-world issues. It integrates optimal policies in various decisionmaking problems and serves as a reference for researchers and industrial practitioners. Furthermore, the book provides sound knowledge of modelling of real-world problems and solution procedure using the various optimisation and statistical techniques for making optimal decisions. The book is meant for teachers, students, researchers and industrialists who are working in the field of materials science, especially operations research and applied statistics.
Book Synopsis Theory of Games and Statistical Decisions by : David A. Blackwell
Download or read book Theory of Games and Statistical Decisions written by David A. Blackwell and published by Courier Corporation. This book was released on 2012-06-14 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: Evaluating statistical procedures through decision and game theory, as first proposed by Neyman and Pearson and extended by Wald, is the goal of this problem-oriented text in mathematical statistics. First-year graduate students in statistics and other students with a background in statistical theory and advanced calculus will find a rigorous, thorough presentation of statistical decision theory treated as a special case of game theory. The work of Borel, von Neumann, and Morgenstern in game theory, of prime importance to decision theory, is covered in its relevant aspects: reduction of games to normal forms, the minimax theorem, and the utility theorem. With this introduction, Blackwell and Professor Girshick look at: Values and Optimal Strategies in Games; General Structure of Statistical Games; Utility and Principles of Choice; Classes of Optimal Strategies; Fixed Sample-Size Games with Finite Ω and with Finite A; Sufficient Statistics and the Invariance Principle; Sequential Games; Bayes and Minimax Sequential Procedures; Estimation; and Comparison of Experiments. A few topics not directly applicable to statistics, such as perfect information theory, are also discussed. Prerequisites for full understanding of the procedures in this book include knowledge of elementary analysis, and some familiarity with matrices, determinants, and linear dependence. For purposes of formal development, only discrete distributions are used, though continuous distributions are employed as illustrations. The number and variety of problems presented will be welcomed by all students, computer experts, and others using statistics and game theory. This comprehensive and sophisticated introduction remains one of the strongest and most useful approaches to a field which today touches areas as diverse as gambling and particle physics.
Book Synopsis Optimal Statistical Decision & Bayesian Inference in Statistical Analysis & Applied Statistical Decision Theory by : Morris H. DeGroot
Download or read book Optimal Statistical Decision & Bayesian Inference in Statistical Analysis & Applied Statistical Decision Theory written by Morris H. DeGroot and published by Wiley. This book was released on 2006-05-19 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Set that includes three works covering statistical decision theory and analysis The three books within this set are Optimal Statistical Decisions, Bayesian Inference in Statistical Analysis, and Applied Statistical Decision Theory. Optimal Statistical Decisions discusses the theory and methodology of decision-making in the field. The volume stands as a clear introduction to Bayesian statistical decision theory. A second book, Bayesian Inference in Statistical Analysis, examines the application and relevance of Bayes' theorem to problems that occur during scientific investigations, where inferences must be made regarding parameter values about which little is known. Key aspects of the Bayesian approach are discussed, including the choice of prior distribution, the problem of nuisance parameters, and the role of sufficient statistics. Applied Statistical Decision Theory covers the development of analytic techniques in the field of statistical decision theory. This classic book was first published in the 1960s.
Book Synopsis Methods of Optimal Statistical Decisions, Optimal Control, and Stochastic Differential Equations by : Ellida M. Khazen
Download or read book Methods of Optimal Statistical Decisions, Optimal Control, and Stochastic Differential Equations written by Ellida M. Khazen and published by Xlibris Corporation. This book was released on 2009-11-16 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides the reader with some insight into the mathematical models of random processes with continuous time, stochastic differential equations and stochastic integrals. An advanced development of the mathematical methods of optimal statistical decisions, statistical sequential analysis, and informational estimation of risks, and new methods and solutions to the important problems of the theory of optimal control are presented. The new original results obtained by this author and published shortly in her numerous scientific-research papers are presented in a systematic way in this book. The book is intended for engineers, students, post-graduate students, and scientist researchers. The presentation of the material is accessible to engineers.
Book Synopsis Methods of Optimal Statistical Decisions, Optimal Control, and Stochastic Differential Equations by : Ellida M. Khazen
Download or read book Methods of Optimal Statistical Decisions, Optimal Control, and Stochastic Differential Equations written by Ellida M. Khazen and published by Xlibris Corporation. This book was released on 2009 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides the reader with some insight into the mathematical models of random processes with continuous time, stochastic differential equations and stochastic integrals. An advanced development of the mathematical methods of optimal statistical decisions, statistical sequential analysis, and informational estimation of risks, and new methods and solutions to the important problems of the theory of optimal control are presented. The new original results obtained by this author and published shortly in her numerous scientific-research papers are presented in a systematic way in this book. The book is intended for engineers, students, post-graduate students, and scientist researchers. The presentation of the material is accessible to engineers.
Book Synopsis Statistical Decision Theory by : F. Liese
Download or read book Statistical Decision Theory written by F. Liese and published by Springer Science & Business Media. This book was released on 2008-12-30 with total page 696 pages. Available in PDF, EPUB and Kindle. Book excerpt: For advanced graduate students, this book is a one-stop shop that presents the main ideas of decision theory in an organized, balanced, and mathematically rigorous manner, while observing statistical relevance. All of the major topics are introduced at an elementary level, then developed incrementally to higher levels. The book is self-contained as it provides full proofs, worked-out examples, and problems. The authors present a rigorous account of the concepts and a broad treatment of the major results of classical finite sample size decision theory and modern asymptotic decision theory. With its broad coverage of decision theory, this book fills the gap between standard graduate texts in mathematical statistics and advanced monographs on modern asymptotic theory.
Book Synopsis Elementary Decision Theory by : Herman Chernoff
Download or read book Elementary Decision Theory written by Herman Chernoff and published by Courier Corporation. This book was released on 1986-01-01 with total page 386 pages. Available in PDF, EPUB and Kindle. Book excerpt: This well-respected introduction to statistics and statistical theory covers data processing, probability and random variables, utility and descriptive statistics, computation of Bayes strategies, models, testing hypotheses, and much more. 1959 edition.
Book Synopsis Statistical Decision Theory and Related Topics V by : Shanti S. Gupta
Download or read book Statistical Decision Theory and Related Topics V written by Shanti S. Gupta and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 535 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Fifth Purdue International Symposium on Statistical Decision The was held at Purdue University during the period of ory and Related Topics June 14-19,1992. The symposium brought together many prominent leaders and younger researchers in statistical decision theory and related areas. The format of the Fifth Symposium was different from the previous symposia in that in addition to the 54 invited papers, there were 81 papers presented in contributed paper sessions. Of the 54 invited papers presented at the sym posium, 42 are collected in this volume. The papers are grouped into a total of six parts: Part 1 - Retrospective on Wald's Decision Theory and Sequential Analysis; Part 2 - Asymptotics and Nonparametrics; Part 3 - Bayesian Analysis; Part 4 - Decision Theory and Selection Procedures; Part 5 - Probability and Probabilistic Structures; and Part 6 - Sequential, Adaptive, and Filtering Problems. While many of the papers in the volume give the latest theoretical developments in these areas, a large number are either applied or creative review papers.
Book Synopsis Optimal Sequentially Planned Decision Procedures by : Norbert Schmitz
Download or read book Optimal Sequentially Planned Decision Procedures written by Norbert Schmitz and published by Springer. This book was released on 1992-10-28 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume is concerned with statistical procedures where the data are collected in sequentially designed groups. The basic premise here is that the expected total sample size is not always the appropriate criterion for evaluating statistical procedures, especially for nonlinear sampling costs (e.g. additive fixed costs) and in clinical trials. In fact, this criterion seems to have been a hindrance to the practical use of Wald's sequential probability ratio test (SPRT) despite its well-known optimum properties. This volume systematically develops decision procedures which retain the possibility of early stopping and remove some of the disadvantages of one-at-a-time sampling. In particular, for generalizations of the SPRT algorithms, methods for computing characteristics (such as operating characteristics or power functions, expected sampling costs, etc.) are developed and implemented. The procedures turn out to be optimal in a Bayesian sense as well as for problems with side conditions (e.g. specified bounds on error probabilities or expected sampling costs). A theory of optimal sampling is developed in order to prove the various properties of the procedures.
Book Synopsis Statistical Decision Rules and Optimal Inference by : N. N. Cencov
Download or read book Statistical Decision Rules and Optimal Inference written by N. N. Cencov and published by American Mathematical Soc.. This book was released on 2000-04-19 with total page 514 pages. Available in PDF, EPUB and Kindle. Book excerpt: None available in plain English.
Book Synopsis Statistical Decision Theory and Related Topics by : Shanti S. Gupta
Download or read book Statistical Decision Theory and Related Topics written by Shanti S. Gupta and published by Academic Press. This book was released on 2014-05-10 with total page 396 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Decision Theory and Related Topics is a collection of the papers presented at the Symposium on Statistical Decision Theory and Related Topics which was held on November 23-25, 1970 at Purdue University. The conference brought together research workers in decision theory and related topics. This volume contains twenty papers presented during the symposium and includes works on molecular studies of evolution, globally optimal procedure for one-sided comparisons, multiple decision theory, outlier detection, empirical Bayes slippage tests, and non-optimality of likelihood ratio tests for sequential detection of signals in Gaussian noise. Mathematicians and statisticians will find the book highly insightful.
Book Synopsis Optimal Statistical Decisions in Highway Safety Related to Geometric Design by : Lonnie Edward Haefner
Download or read book Optimal Statistical Decisions in Highway Safety Related to Geometric Design written by Lonnie Edward Haefner and published by . This book was released on 1970 with total page 468 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Statistical Decision Theory by : James Berger
Download or read book Statistical Decision Theory written by James Berger and published by Springer Science & Business Media. This book was released on 2013-04-17 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: Decision theory is generally taught in one of two very different ways. When of opti taught by theoretical statisticians, it tends to be presented as a set of mathematical techniques mality principles, together with a collection of various statistical procedures. When useful in establishing the optimality taught by applied decision theorists, it is usually a course in Bayesian analysis, showing how this one decision principle can be applied in various practical situations. The original goal I had in writing this book was to find some middle ground. I wanted a book which discussed the more theoretical ideas and techniques of decision theory, but in a manner that was constantly oriented towards solving statistical problems. In particular, it seemed crucial to include a discussion of when and why the various decision prin ciples should be used, and indeed why decision theory is needed at all. This original goal seemed indicated by my philosophical position at the time, which can best be described as basically neutral. I felt that no one approach to decision theory (or statistics) was clearly superior to the others, and so planned a rather low key and impartial presentation of the competing ideas. In the course of writing the book, however, I turned into a rabid Bayesian. There was no single cause for this conversion; just a gradual realization that things seemed to ultimately make sense only when looked at from the Bayesian viewpoint.
Book Synopsis Optimization Techniques in Statistics by : Jagdish S. Rustagi
Download or read book Optimization Techniques in Statistics written by Jagdish S. Rustagi and published by Elsevier. This book was released on 2014-05-19 with total page 359 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistics help guide us to optimal decisions under uncertainty. A large variety of statistical problems are essentially solutions to optimization problems. The mathematical techniques of optimization are fundamentalto statistical theory and practice. In this book, Jagdish Rustagi provides full-spectrum coverage of these methods, ranging from classical optimization and Lagrange multipliers, to numerical techniques using gradients or direct search, to linear, nonlinear, and dynamic programming using the Kuhn-Tucker conditions or the Pontryagin maximal principle. Variational methods and optimization in function spaces are also discussed, as are stochastic optimization in simulation, including annealing methods. The text features numerous applications, including: Finding maximum likelihood estimates Markov decision processes Programming methods used to optimize monitoring of patients in hospitals Derivation of the Neyman-Pearson lemma The search for optimal designs Simulation of a steel mill Suitable as both a reference and a text, this book will be of interest to advanced undergraduate or beginning graduate students in statistics, operations research, management and engineering sciences, and related fields. Most of the material can be covered in one semester by students with a basic background in probability and statistics. Key Features * Covers optimization from traditional methods to recent developments such as Karmarkars algorithm and simulated annealing * Develops a wide range of statistical techniques in the unified context of optimization * Discusses applications such as optimizing monitoring of patients and simulating steel mill operations * Treats numerical methods and applications Includes exercises and references for each chapter * Covers topics such as linear, nonlinear, and dynamic programming, variational methods, and stochastic optimization
