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Statistical Decision Functions
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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 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 Introduction to Statistical Decision Theory by : Silvia Bacci
Download or read book Introduction to Statistical Decision Theory written by Silvia Bacci and published by CRC Press. This book was released on 2019-07-11 with total page 305 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to Statistical Decision Theory: Utility Theory and Causal Analysis provides the theoretical background to approach decision theory from a statistical perspective. It covers both traditional approaches, in terms of value theory and expected utility theory, and recent developments, in terms of causal inference. The book is specifically designed to appeal to students and researchers that intend to acquire a knowledge of statistical science based on decision theory. Features Covers approaches for making decisions under certainty, risk, and uncertainty Illustrates expected utility theory and its extensions Describes approaches to elicit the utility function Reviews classical and Bayesian approaches to statistical inference based on decision theory Discusses the role of causal analysis in statistical decision theory
Book Synopsis Statistical Decision Theory and Bayesian Analysis by : James O. Berger
Download or read book Statistical Decision Theory and Bayesian Analysis written by James O. Berger and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 633 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this new edition the author has added substantial material on Bayesian analysis, including lengthy new sections on such important topics as empirical and hierarchical Bayes analysis, Bayesian calculation, Bayesian communication, and group decision making. With these changes, the book can be used as a self-contained introduction to Bayesian analysis. In addition, much of the decision-theoretic portion of the text was updated, including new sections covering such modern topics as minimax multivariate (Stein) estimation.
Book Synopsis Statistical Decision Functions by : Abraham Wald
Download or read book Statistical Decision Functions written by Abraham Wald and published by . This book was released on 1961 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: The general statistical decision problem: definitions and preliminary discussion; Zero sum two-person games with infinitely many strategies; Development of a general theory of statistical decision functions; Properties of bayes solutions when the chance variables are independently and identically distributed and the cost of experimentation is proportional to the number of observations; Application of the general theory to various special cases.
Book Synopsis Introduction to Statistical Decision Theory by : John Winsor Pratt
Download or read book Introduction to Statistical Decision Theory written by John Winsor Pratt and published by . This book was released on 1994 with total page 875 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Statistical Decision Problems by : Michael Zabarankin
Download or read book Statistical Decision Problems written by Michael Zabarankin and published by Springer Science & Business Media. This book was released on 2013-12-16 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Decision Problems presents a quick and concise introduction into the theory of risk, deviation and error measures that play a key role in statistical decision problems. It introduces state-of-the-art practical decision making through twenty-one case studies from real-life applications. The case studies cover a broad area of topics and the authors include links with source code and data, a very helpful tool for the reader. In its core, the text demonstrates how to use different factors to formulate statistical decision problems arising in various risk management applications, such as optimal hedging, portfolio optimization, cash flow matching, classification, and more. The presentation is organized into three parts: selected concepts of statistical decision theory, statistical decision problems, and case studies with portfolio safeguard. The text is primarily aimed at practitioners in the areas of risk management, decision making, and statistics. However, the inclusion of a fair bit of mathematical rigor renders this monograph an excellent introduction to the theory of general error, deviation, and risk measures for graduate students. It can be used as supplementary reading for graduate courses including statistical analysis, data mining, stochastic programming, financial engineering, to name a few. The high level of detail may serve useful to applied mathematicians, engineers, and statisticians interested in modeling and managing risk in various applications.
Book Synopsis Asymptotic Methods in Statistical Decision Theory by : Lucien Le Cam
Download or read book Asymptotic Methods in Statistical Decision Theory written by Lucien Le Cam and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 767 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book grew out of lectures delivered at the University of California, Berkeley, over many years. The subject is a part of asymptotics in statistics, organized around a few central ideas. The presentation proceeds from the general to the particular since this seemed the best way to emphasize the basic concepts. The reader is expected to have been exposed to statistical thinking and methodology, as expounded for instance in the book by H. Cramer [1946] or the more recent text by P. Bickel and K. Doksum [1977]. Another pos sibility, closer to the present in spirit, is Ferguson [1967]. Otherwise the reader is expected to possess some mathematical maturity, but not really a great deal of detailed mathematical knowledge. Very few mathematical objects are used; their assumed properties are simple; the results are almost always immediate consequences of the definitions. Some objects, such as vector lattices, may not have been included in the standard background of a student of statistics. For these we have provided a summary of relevant facts in the Appendix. The basic structures in the whole affair are systems that Blackwell called "experiments" and "transitions" between them. An "experiment" is a mathe matical abstraction intended to describe the basic features of an observational process if that process is contemplated in advance of its implementation. Typically, an experiment consists of a set E> of theories about what may happen in the observational process.
Book Synopsis Introduction to Statistical Decision Theory by : Silvia Bacci
Download or read book Introduction to Statistical Decision Theory written by Silvia Bacci and published by CRC Press. This book was released on 2019-07-11 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to Statistical Decision Theory: Utility Theory and Causal Analysis provides the theoretical background to approach decision theory from a statistical perspective. It covers both traditional approaches, in terms of value theory and expected utility theory, and recent developments, in terms of causal inference. The book is specifically designed to appeal to students and researchers that intend to acquire a knowledge of statistical science based on decision theory. Features Covers approaches for making decisions under certainty, risk, and uncertainty Illustrates expected utility theory and its extensions Describes approaches to elicit the utility function Reviews classical and Bayesian approaches to statistical inference based on decision theory Discusses the role of causal analysis in statistical decision theory
Book Synopsis Learning to Read and Write in One Elementary School by : Connie Juel
Download or read book Learning to Read and Write in One Elementary School written by Connie Juel and published by Springer Science & Business Media. This book was released on 1993-10-22 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt: This unique book presents a four-year longitudinal study of the literacy development of children attending an Austin, Texas area elementary school. The reading and writing development of this microcosm of "at-risk" children was followed as they progressed from first through fourth grade. The author poses the question, "What skills and abilities of the child, and what classroom factors, appear to foster literacy development?" Included here are the author's models of reading and writing acquisition, and application of these models to six children: three with literacy problems and three with successful literacy development. Interviews with the children are presented along with measures of their cognitive development and skills, samples of their reading and writing from and throughout the four year study, and an examination of their successes and failures in relations to the models presented in earlier chapters. Additionally, one chapter examines school-related factors that may play a role in the children's reading development. The book is intended for graduate students at all levels and literacy researchers who are interested in the process of literacy acquisition as it occurs in the school setting.
Book Synopsis Applied Statistical Decision Theory by : Howard Raiffa
Download or read book Applied Statistical Decision Theory written by Howard Raiffa and published by . This book was released on 1966 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Set Functions, Games and Capacities in Decision Making by : Michel Grabisch
Download or read book Set Functions, Games and Capacities in Decision Making written by Michel Grabisch and published by Springer. This book was released on 2016-06-15 with total page 482 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book provides a thorough treatment of set functions, games and capacities as well as integrals with respect to capacities and games, in a mathematical rigorous presentation and in view of application to decision making. After a short chapter introducing some required basic knowledge (linear programming, polyhedra, ordered sets) and notation, the first part of the book consists of three long chapters developing the mathematical aspects. This part is not related to a particular application field and, by its neutral mathematical style, is useful to the widest audience. It gathers many results and notions which are scattered in the literature of various domains (game theory, decision, combinatorial optimization and operations research). The second part consists of three chapters, applying the previous notions in decision making and modelling: decision under uncertainty, decision with multiple criteria, possibility theory and Dempster-Shafer theory.
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 All of Statistics by : Larry Wasserman
Download or read book All of Statistics written by Larry Wasserman and published by Springer Science & Business Media. This book was released on 2013-12-11 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt: Taken literally, the title "All of Statistics" is an exaggeration. But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines. The book includes modern topics like non-parametric curve estimation, bootstrapping, and classification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analysing data.
Book Synopsis Introduction to Statistical Pattern Recognition by : Keinosuke Fukunaga
Download or read book Introduction to Statistical Pattern Recognition written by Keinosuke Fukunaga and published by Elsevier. This book was released on 2013-10-22 with total page 606 pages. Available in PDF, EPUB and Kindle. Book excerpt: This completely revised second edition presents an introduction to statistical pattern recognition. Pattern recognition in general covers a wide range of problems: it is applied to engineering problems, such as character readers and wave form analysis as well as to brain modeling in biology and psychology. Statistical decision and estimation, which are the main subjects of this book, are regarded as fundamental to the study of pattern recognition. This book is appropriate as a text for introductory courses in pattern recognition and as a reference book for workers in the field. Each chapter contains computer projects as well as exercises.
Book Synopsis STATISTICAL INFERENCE by : M. RAJAGOPALAN
Download or read book STATISTICAL INFERENCE written by M. RAJAGOPALAN and published by PHI Learning Pvt. Ltd.. This book was released on 2012-07-08 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: Intended as a text for the postgraduate students of statistics, this well-written book gives a complete coverage of Estimation theory and Hypothesis testing, in an easy-to-understand style. It is the outcome of the authors’ teaching experience over the years. The text discusses absolutely continuous distributions and random sample which are the basic concepts on which Statistical Inference is built up, with examples that give a clear idea as to what a random sample is and how to draw one such sample from a distribution in real-life situations. It also discusses maximum-likelihood method of estimation, Neyman’s shortest confidence interval, classical and Bayesian approach. The difference between statistical inference and statistical decision theory is explained with plenty of illustrations that help students obtain the necessary results from the theory of probability and distributions, used in inference.
Book Synopsis Convex Functions, Partial Orderings, and Statistical Applications by : Josip E. Peajcariaac
Download or read book Convex Functions, Partial Orderings, and Statistical Applications written by Josip E. Peajcariaac and published by Academic Press. This book was released on 1992-06-03 with total page 485 pages. Available in PDF, EPUB and Kindle. Book excerpt: This research-level book presents up-to-date information concerning recent developments in convex functions and partial orderings and some applications in mathematics, statistics, and reliability theory. The book will serve researchers in mathematical and statistical theory and theoretical and applied reliabilists. Presents classical and newly published results on convex functions and related inequalities Explains partial ordering based on arrangement and their applications in mathematics, probability, statsitics, and reliability Demonstrates the connection of partial ordering with other well-known orderings such as majorization and Schur functions Will generate further research and applications
