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Fb2 Decision Theory: Principles and Approaches ePub

by Giovanni Parmigiani,Lurdes Inoue

Category: Mathematics
Subcategory: Science books
Author: Giovanni Parmigiani,Lurdes Inoue
ISBN: 047149657X
ISBN13: 978-0471496571
Language: English
Publisher: Wiley; 1 edition (May 26, 2009)
Pages: 404
Fb2 eBook: 1378 kb
ePub eBook: 1183 kb
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by Giovanni Parmigiani (Author), Lurdes Inoue (Author). This book presents an overview of the fundamental concepts and outcomes of rational decision making under uncertainty, highlighting the implications for statistical practice.

by Giovanni Parmigiani (Author), Lurdes Inoue (Author). ISBN-13: 978-0471496571. 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.

Giovanni Parmigiani is the author of Decision Theory: Principles and Approaches, published by Wiley. Lurdes Yoshiko Tani Inoue is a Brazilian-born statistician of Japanese descent, who specializes in Bayesian inference

Giovanni Parmigiani is the author of Decision Theory: Principles and Approaches, published by Wiley. Lurdes Yoshiko Tani Inoue is a Brazilian-born statistician of Japanese descent, who specializes in Bayesian inference. She works as a professor of biostatistics in the University of Washington School of Public Health.

Lurdes Y. T. Inoue University of Washington, Seattle, USA with contributions b. Inoue University of Washington, Seattle, USA with contributions by. Hedibert F. Lopes University of Chicago, USA. A John Wiley and Sons, Lt. Publication. p. cm. Includes bibliographical references and index. ISBN 978-0-471-49657-1 (cloth) 1. Statistical decision. 2. Axiomatic set theory. 3. Experimental design.

Decision Theory: Principles and approaches. Lurdes Yoshiko Tani INOUE. Johns Hopkins University, Baltimore, MD, USA. University of Washington, Seattle, WA, USA. with contributions from Hedibert Lopes. The goal of this book is to give an overview of fundamental ideas and results about rational decision making under uncertainty, highlighting the implications of these results for the philosophy and practice of statistics. The book grew from lecture notes from graduate courses taught at the Institute of Statistics and Decision Sciences at Duke, at the Johns Hopkins School of Public Health, and at the University of Washington. by Giovanni Parmigiani and Lurdes Inoue. 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.

Decision Theory book. Start by marking Decision Theory: Principles and Approaches as Want to Read: Want to Read savin. ant to Read.

Lurdes Yoshiko Tani Inoue is a Brazilian-born statistician of Japanese descent, who specializes in Bayesian inference. She works as a professor of biostatistics in the University of Washington School of Public Health

Decision theory provides a formal framework for making logical choices in the face of uncertainty.

Decision theory provides a formal framework for making logical choices in the face of uncertainty.

Find many great new & used options and get the best deals for Decision Theory: Principles and Approaches by Giovanni . Lurdes Inoue, Giovanni Parmigiani. Place of Publication.

Lurdes Inoue, Giovanni Parmigiani.

Decision theory provides a formal framework for making logicalchoices in the face of uncertainty. Given a set of alternatives, aset 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 andoutcomes of rational decision making under uncertainty,highlighting the implications for statistical practice.

The authors have developed a series of self contained chaptersfocusing on bridging the gaps between the different fields thathave contributed to rational decision making and presenting ideasin a unified framework and notation while respecting andhighlighting the different and sometimes conflictingperspectives.

This book:

Provides a rich collection of techniques and procedures.Discusses the foundational aspects and modern daypractice.Links foundations to practical applications in biostatistics,computer science, engineering and economics.Presents different perspectives and controversies to encouragereaders to form their own opinion of decision making andstatistics.

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

Comments to eBook Decision Theory: Principles and Approaches
JoJosho
There have been many books on decision theory going all the way back to Wald in the 1940s. We have the texts by Blackwell and Girshick, Luce and Raiffa, Raiffa and Schlaifer, DeGroot, Berger, Wald, Ferguson, and Chernoff and Moses to name some of the classics. Parmigiani and Inoue provide an up-to-date acount on the subject. New ultiity fuinctions such as QALY (quality of life years) are introduced and the chapters 2-6 provide the foundations of the Bayesian approach to decision theory. Then chapters 7-11 provide the theory from the Bayesian viewpoint. They include the concept of admissibility and Stein's famous shrinkage estimators that show the maximum likelihood estimator for a multivariate mean vector is not admissible (3 or more dimensions).

The third section titled Optimal Design deals with multistage decision problems and introduces dynamic programming as a technique to solve some of these problems.
Conjukus
This textbook covers all of the basics in decision theory. It is clear and thorough. One especially nice thing about this book is that it collects several results in one place that aren't covered in much detail in many statistics texts: the Stein phenomenon, complete class theorems, and state-dependent utilities, to name a few. I'd pair this with Schervish's Theory of Statistics and Gelman and Hill's Data Analysis Using Regression and Multilevel/Hierarchical Models for a three-pack covering the core of Bayesian statistics -- decision theory, statistical theory and applied regression modeling.
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