Statistical Decision Theory and Bayesian Analysis

Statistical Decision Theory and Bayesian Analysis

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 ...

Author: James O. Berger

Publisher: Springer Science & Business Media

ISBN: 9781475742862

Category: Mathematics

Page: 618

View: 312

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.
Categories: Mathematics

Statistical Decision Theory and Related Topics V

Statistical Decision Theory and Related Topics V

Of the 54 invited papers presented at the sym posium, 42 are collected in this volume.

Author: Shanti S. Gupta

Publisher: Springer

ISBN: 1461276098

Category: Business & Economics

Page: 537

View: 259

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.
Categories: Business & Economics

Probability Statistics and Decision Making in the Atmospheric Sciences

Probability  Statistics  and Decision Making in the Atmospheric Sciences

Despite the increasingly pervasive nature of such applications. very few book length treatments of probabilistic and statistical topics of particular interest to atmospheric scientists have appeared (especially inEnglish) since the ...

Author: Allan Murphy

Publisher: CRC Press

ISBN: 0367284332

Category: Atmosphere

Page: 547

View: 395

Methodology drawn from the fields of probability. statistics and decision making plays an increasingly important role in the atmosphericsciences. both in basic and applied research and in experimental and operational studies. Applications of such methodology can be found in almost every facet of the discipline. from the most theoretical and global (e.g., atmospheric predictability. global climate modeling) to the most practical and local (e.g., crop-weather modeling forecast evaluation). Almost every issue of the multitude of journals published by the atmospheric sciences community now contain some or more papers involving applications of concepts and/or methodology from the fields of probability and statistics. Despite the increasingly pervasive nature of such applications. very few book length treatments of probabilistic and statistical topics of particular interest to atmospheric scientists have appeared (especially inEnglish) since the publication of the pioneering works of Brooks andCarruthers (Handbook of Statistical Methods in Meteorology) in 1953 and Panofsky and Brier-(some Applications of)statistics to Meteor) in 1958. As a result. many relatively recent developments in probability and statistics are not well known to atmospheric scientists and recent work in active areas of meteorological research involving significant applications of probabilistic and statistical methods are not familiar to the meteorological community as a whole.
Categories: Atmosphere

Probability and Statistical Decision Theory

Probability and Statistical Decision Theory

Proceedings of the 4th Pannonian Symposium on Mathematical Statistics, Bad Tatzmannsdorf, Austria, 4-10 September 1983, Volume A.

Author: F. Konecny

Publisher: Springer

ISBN: 9027720894

Category: Mathematics

Page: 340

View: 945

Proceedings of the 4th Pannonian Symposium on Mathematical Statistics, Bad Tatzmannsdorf, Austria, 4-10 September 1983, Volume A.
Categories: Mathematics

Probability and Statistical Decision Theory

Probability and Statistical Decision Theory

About 130 participants from 17 countries took part in this Fourth Symposium, and 92 lectures were presented. This volume contains 21 reviewed contributions which cover various aspects of the application of mathematical statistics.

Author: F. Konecny

Publisher:

ISBN: OCLC:632769790

Category:

Page:

View: 439

Categories:

Probability and Statistical Decision Theory

Probability and Statistical Decision Theory

Proceedings of the 4th Pannonian Symposium on Mathematical Statistics, Bad Tatzmannsdorf, Austria, 4-10 September 1983, Volume A.

Author: F. Konecny

Publisher: Springer

ISBN: 9789027720894

Category: Mathematics

Page: 360

View: 437

Proceedings of the 4th Pannonian Symposium on Mathematical Statistics, Bad Tatzmannsdorf, Austria, 4-10 September 1983, Volume A.
Categories: Mathematics

Statistical Decision Theory

Statistical Decision Theory

The original goal I had in writing this book was to find some middle ground.

Author: James Berger

Publisher: Springer Science & Business Media

ISBN: 9781475717273

Category: Mathematics

Page: 428

View: 245

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.
Categories: Mathematics

Introduction to Statistical Decision Theory

Introduction to Statistical Decision Theory

The book is specifically designed to appeal to students and researchers that intend to acquire a knowledge of statistical science based on decision theory.

Author: Silvia Bacci

Publisher: CRC Press

ISBN: 9781351621397

Category: Mathematics

Page: 287

View: 225

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
Categories: Mathematics

Statistical Decision Theory in Adaptive Control Systems

Statistical Decision Theory in Adaptive Control Systems

This book is recommended for students and researchers concerned with statistical decision theory in adaptive control systems.

Author: Yoshikazu Sawaragi

Publisher: Elsevier

ISBN: 9781483266770

Category: Technology & Engineering

Page: 230

View: 450

Mathematics in Science and Engineering, Volume 39: Statistical Decision Theory in Adaptive Control Systems focuses on the combination of control theory with statistical decision theory. This volume is divided into nine chapters. Chapter 1 reviews the history of control theory and introduces statistical decision theory. The mathematical description of random processes is covered in Chapter 2. In Chapter 3, the basic concept of statistical decision theory is treated, while in Chapter 4, the method of solving statistical decision problems is described. The application of statistical decision concepts to control problems is explained in Chapter 5. Chapter 6 elaborates a method of designing an adaptive control system. An application of the sequential decision procedure to the design of decision adaptive control systems is illustrated in Chapter 7. Chapter 8 is devoted to the description of a method of the adaptive adjustment of parameters contained in nonlinear control systems, followed by a discussion of the future problems in applications of statistical decision theory to control processes in the last chapter. This book is recommended for students and researchers concerned with statistical decision theory in adaptive control systems.
Categories: Technology & Engineering

Decision Theory

Decision Theory

Decision Theory is fundamental to all scientific disciplines, including biostatistics, computer science, economics and engineering. Anyone interested in the whys and wherefores of statistical science will find much to enjoy in this book.

Author: Giovanni Parmigiani

Publisher: John Wiley & Sons

ISBN: 9780470746677

Category: Mathematics

Page: 402

View: 387

Decision theory provides a formal framework for making logical choices in the face of uncertainty. Given a set of alternatives, a set of consequences, and a correspondence between those sets, decision theory offers conceptually simple procedures for choice. This book presents an overview of the fundamental concepts and outcomes of rational decision making under uncertainty, highlighting the implications for statistical practice. The authors have developed a series of self contained chapters focusing on bridging the gaps between the different fields that have contributed to rational decision making and presenting ideas in a unified framework and notation while respecting and highlighting the different and sometimes conflicting perspectives. This book: Provides a rich collection of techniques and procedures. Discusses the foundational aspects and modern day practice. Links foundations to practical applications in biostatistics, computer science, engineering and economics. Presents different perspectives and controversies to encourage readers to form their own opinion of decision making and statistics. Decision Theory is fundamental to all scientific disciplines, including biostatistics, computer science, economics and engineering. Anyone interested in the whys and wherefores of statistical science will find much to enjoy in this book.
Categories: Mathematics

Fuzzy Statistical Decision Making

Fuzzy Statistical Decision Making

This book offers a comprehensive reference guide to fuzzy statistics and fuzzy decision-making techniques.

Author: Cengiz Kahraman

Publisher: Springer

ISBN: 9783319390147

Category: Technology & Engineering

Page: 356

View: 303

This book offers a comprehensive reference guide to fuzzy statistics and fuzzy decision-making techniques. It provides readers with all the necessary tools for making statistical inference in the case of incomplete information or insufficient data, where classical statistics cannot be applied. The respective chapters, written by prominent researchers, explain a wealth of both basic and advanced concepts including: fuzzy probability distributions, fuzzy frequency distributions, fuzzy Bayesian inference, fuzzy mean, mode and median, fuzzy dispersion, fuzzy p-value, and many others. To foster a better understanding, all the chapters include relevant numerical examples or case studies. Taken together, they form an excellent reference guide for researchers, lecturers and postgraduate students pursuing research on fuzzy statistics. Moreover, by extending all the main aspects of classical statistical decision-making to its fuzzy counterpart, the book presents a dynamic snapshot of the field that is expected to stimulate new directions, ideas and developments.
Categories: Technology & Engineering

Statistical Decision Theory and Related Topics III

Statistical Decision Theory and Related Topics III

This volume contains the research papers presented at the symposium and includes works on general decision theory, multiple decision theory, optimum experimental design, sequential and adaptive inference, Bayesian analysis, robustness, and ...

Author: Shanti S. Gupta

Publisher: Academic Press

ISBN: 9781483259550

Category: Mathematics

Page: 550

View: 493

Statistical Decision Theory and Related Topics III, Volume 2 is a collection of papers presented at the Third Purdue Symposium on Statistical Decision Theory and Related Topics, held at Purdue University in June 1981. The symposium brought together many prominent leaders and a number of younger researchers in statistical decision theory and related areas. This volume contains the research papers presented at the symposium and includes works on general decision theory, multiple decision theory, optimum experimental design, sequential and adaptive inference, Bayesian analysis, robustness, and large sample theory. These research areas have seen rapid developments since the preceding Purdue Symposium in 1976, developments reflected by the variety and depth of the works in this volume. Statisticians and mathematicians will find the book very insightful.
Categories: Mathematics