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Foundations of Info-Metrics : Modeling, Inference, and Imperfect Information by Amos Golan (2017, Trade Paperback)
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About this product
Product Identifiers
PublisherOxford University Press, Incorporated
ISBN-100199349533
ISBN-139780199349531
eBay Product ID (ePID)239728486
Product Key Features
Number of Pages496 Pages
Publication NameFoundations of Info-Metrics : Modeling, Inference, and Imperfect Information
LanguageEnglish
Publication Year2017
SubjectProbability & Statistics / General, Econometrics, Logic
TypeTextbook
Subject AreaMathematics, Philosophy, Business & Economics
AuthorAmos Golan
FormatTrade Paperback
Dimensions
Item Height1.2 in
Item Weight28.5 Oz
Item Length6.1 in
Item Width9.1 in
Additional Product Features
Intended AudienceScholarly & Professional
LCCN2016-052820
Dewey Edition23
Reviews"Decision making under uncertainty is central to a number of different disciplines from neuro-science to psychology, sociology, politics and economics, and Dr. Golan provides a comprehensive account of the foundational issues involved and offers a synthesis that should be of interest to researchers across many fields. The Info-Metrics approach advocated acknowledges the limited nature of information available and provides a framework that could be used in many contexts." - Hashem Pesaran, John Elliot Distinguished Chair in Economics at USC, and Fellow of Trinity College Cambridge "Amos Golan has written a remarkably comprehensive and scholarly textbook on information theory as a foundation for inference in economics and the natural sciences. I expect that it will long remain a valuable resource for teachers, students, and practitioners." - John Harte, Professor of Ecosystem Sciences, UC Berkeley "The book provides a comprehensive coverage of all major topics built on or enveloping the entropy maximization principle. While offering appropriate technical depths on the core topics, it features several application case studies at a level beyond any existing books on entropy maximization. Its contemporary feel is among the most attractive aspects of this book, making it ideal for students and researchers alike." - Min Chen, Professor of Scientific Visualization, University of Oxford "The publication of Foundations of Info-Metrics is a paradigm-changing event. Golan systematically shows the generality and power of the method, illustrated by many important and detailed examples and accompanied by a careful comparison of info-metrics with other widely used data modeling systems. For scientists and social scientists working with incomplete, noisy, and inadequate data, which is all of us, this book provides an essential breakthrough to new perspectives." - Duncan K. Foley Leo Model Professor of Economics, New School for Social Research "From the founder of info-metrics comes this overview of their foundations. This book addresses in a very readable way the fundamental logical, philosophical and practical issues of info-metrics, including causal inference, information processing, and modeling/theory building in the sciences." - J. Michael Dunn, Indiana University, Founding Dean Emeritus and Professor Emeritus of the School of Informatics and Computing, and Oscar Ewing Professor Emeritus of Philosophy, "Amos Golan has written a remarkably comprehensive and scholarly textbook on information theory as a foundation for inference in economics and the natural sciences. I expect that it will long remain a valuable resource for teachers, students, and practitioners." - John Harte, Professor of Ecosystem Sciences, UC Berkeley "The book provides a comprehensive coverage of all major topics built on or enveloping the entropy maximization principle. While offering appropriate technical depths on the core topics, it features several application case studies at a level beyond any existing books on entropy maximization. Its contemporary feel is among the most attractive aspects of this book, making it ideal for students and researchers alike." - Min Chen, Professor of Scientific Visualization, University of Oxford "The publication of Foundations of Info-Metrics is a paradigm-changing event. Golan systematically shows the generality and power of the method, illustrated by many important and detailed examples and accompanied by a careful comparison of info-metrics with other widely used data modeling systems. For scientists and social scientists working with incomplete, noisy, and inadequate data, which is all of us, this book provides an essential breakthrough to new perspectives." - Duncan K. Foley Leo Model Professor of Economics, New School for Social Research "From the founder of info-metrics comes this overview of their foundations. This book addresses in a very readable way the fundamental logical, philosophical and practical issues of info-metrics, including causal inference, information processing, and modeling/theory building in the sciences." - J. Michael Dunn, Indiana University, Founding Dean Emeritus and Professor Emeritus of the School of Informatics and Computing, and Oscar Ewing Professor Emeritus of Philosophy, "It provides all the necessary tools and building blocks for using the info-metrics framework for solving problems, making decisions, and constructing models under incomplete information. The multidisciplinary applications provide a hands-on experience for the reader. That experience can be enhanced via the exercises and problems at the end of each chapter." -- Kathy Wolcott, MathSciNet "Decision making under uncertainty is central to a number of different disciplines from neuro-science to psychology, sociology, politics and economics, and Dr. Golan provides a comprehensive account of the foundational issues involved and offers a synthesis that should be of interest to researchers across many fields. The Info-Metrics approach advocated acknowledges the limited nature of information available and provides a framework that could be used in many contexts." - Hashem Pesaran, John Elliot Distinguished Chair in Economics at USC, and Fellow of Trinity College Cambridge "Amos Golan has written a remarkably comprehensive and scholarly textbook on information theory as a foundation for inference in economics and the natural sciences. I expect that it will long remain a valuable resource for teachers, students, and practitioners." - John Harte, Professor of Ecosystem Sciences, UC Berkeley "The book provides a comprehensive coverage of all major topics built on or enveloping the entropy maximization principle. While offering appropriate technical depths on the core topics, it features several application case studies at a level beyond any existing books on entropy maximization. Its contemporary feel is among the most attractive aspects of this book, making it ideal for students and researchers alike." - Min Chen, Professor of Scientific Visualization, University of Oxford "The publication of Foundations of Info-Metrics is a paradigm-changing event. Golan systematically shows the generality and power of the method, illustrated by many important and detailed examples and accompanied by a careful comparison of info-metrics with other widely used data modeling systems. For scientists and social scientists working with incomplete, noisy, and inadequate data, which is all of us, this book provides an essential breakthrough to new perspectives." - Duncan K. Foley Leo Model Professor of Economics, New School for Social Research "From the founder of info-metrics comes this overview of their foundations. This book addresses in a very readable way the fundamental logical, philosophical and practical issues of info-metrics, including causal inference, information processing, and modeling/theory building in the sciences." - J. Michael Dunn, Indiana University, Founding Dean Emeritus and Professor Emeritus of the School of Informatics and Computing, and Oscar Ewing Professor Emeritus of Philosophy "Each chapter comes with a set of carefully designed exercises and problems. I am also delighted to see a dedicated info-metrics website that provides codes and data for all examples in this book, interactive examples, and additional materials. I have no doubt that this book should be of interest to researchers in many fields of social and natural science and is an ideal choice for an introductory course in information theory." - Ximing Wu, American Journal of Agricultural Economics, "It provides all the necessary tools and building blocks for using the info-metrics framework for solving problems, making decisions, and constructing models under incomplete information. The multidisciplinary applications provide a hands-on experience for the reader. That experience can be enhanced via the exercises and problems at the end of each chapter." -- Kathy Wolcott, MathSciNet "Decision making under uncertainty is central to a number of different disciplines from neuro-science to psychology, sociology, politics and economics, and Dr. Golan provides a comprehensive account of the foundational issues involved and offers a synthesis that should be of interest to researchers across many fields. The Info-Metrics approach advocated acknowledges the limited nature of information available and provides a framework that could be used in many contexts." - Hashem Pesaran, John Elliot Distinguished Chair in Economics at USC, and Fellow of Trinity College Cambridge "Amos Golan has written a remarkably comprehensive and scholarly textbook on information theory as a foundation for inference in economics and the natural sciences. I expect that it will long remain a valuable resource for teachers, students, and practitioners." - John Harte, Professor of Ecosystem Sciences, UC Berkeley "The book provides a comprehensive coverage of all major topics built on or enveloping the entropy maximization principle. While offering appropriate technical depths on the core topics, it features several application case studies at a level beyond any existing books on entropy maximization. Its contemporary feel is among the most attractive aspects of this book, making it ideal for students and researchers alike." - Min Chen, Professor of Scientific Visualization, University of Oxford "The publication of Foundations of Info-Metrics is a paradigm-changing event. Golan systematically shows the generality and power of the method, illustrated by many important and detailed examples and accompanied by a careful comparison of info-metrics with other widely used data modeling systems. For scientists and social scientists working with incomplete, noisy, and inadequate data, which is all of us, this book provides an essential breakthrough to new perspectives." - Duncan K. Foley Leo Model Professor of Economics, New School for Social Research "From the founder of info-metrics comes this overview of their foundations. This book addresses in a very readable way the fundamental logical, philosophical and practical issues of info-metrics, including causal inference, information processing, and modeling/theory building in the sciences." - J. Michael Dunn, Indiana University, Founding Dean Emeritus and Professor Emeritus of the School of Informatics and Computing, and Oscar Ewing Professor Emeritus of Philosophy, "Info-metrics provides a unifying framework for inference and broadens the set of tools available to policy researchers. Foundations of Info-Metrics is an engaging and accessible treatment full of applications that shows the strengths of the approach for situations where traditional methods may struggle or are difficult to apply. More than 20 years since the development of maximum entropy econometrics, this book should attract new audiences to the ideas of info-metrics."-- Journal of Policy Analysis and Management "It provides all the necessary tools and building blocks for using the info-metrics framework for solving problems, making decisions, and constructing models under incomplete information. The multidisciplinary applications provide a hands-on experience for the reader. That experience can be enhanced via the exercises and problems at the end of each chapter." -- Kathy Wolcott, MathSciNet "Decision making under uncertainty is central to a number of different disciplines from neuro-science to psychology, sociology, politics and economics, and Dr. Golan provides a comprehensive account of the foundational issues involved and offers a synthesis that should be of interest to researchers across many fields. The Info-Metrics approach advocated acknowledges the limited nature of information available and provides a framework that could be used in many contexts." - Hashem Pesaran, John Elliot Distinguished Chair in Economics at USC, and Fellow of Trinity College Cambridge "Amos Golan has written a remarkably comprehensive and scholarly textbook on information theory as a foundation for inference in economics and the natural sciences. I expect that it will long remain a valuable resource for teachers, students, and practitioners." - John Harte, Professor of Ecosystem Sciences, UC Berkeley "The book provides a comprehensive coverage of all major topics built on or enveloping the entropy maximization principle. While offering appropriate technical depths on the core topics, it features several application case studies at a level beyond any existing books on entropy maximization. Its contemporary feel is among the most attractive aspects of this book, making it ideal for students and researchers alike." - Min Chen, Professor of Scientific Visualization, University of Oxford "The publication of Foundations of Info-Metrics is a paradigm-changing event. Golan systematically shows the generality and power of the method, illustrated by many important and detailed examples and accompanied by a careful comparison of info-metrics with other widely used data modeling systems. For scientists and social scientists working with incomplete, noisy, and inadequate data, which is all of us, this book provides an essential breakthrough to new perspectives." - Duncan K. Foley Leo Model Professor of Economics, New School for Social Research "From the founder of info-metrics comes this overview of their foundations. This book addresses in a very readable way the fundamental logical, philosophical and practical issues of info-metrics, including causal inference, information processing, and modeling/theory building in the sciences." - J. Michael Dunn, Indiana University, Founding Dean Emeritus and Professor Emeritus of the School of Informatics and Computing, and Oscar Ewing Professor Emeritus of Philosophy "Each chapter comes with a set of carefully designed exercises and problems. I am also delighted to see a dedicated info-metrics website that provides codes and data for all examples in this book, interactive examples, and additional materials. I have no doubt that this book should be of interest to researchers in many fields of social and natural science and is an ideal choice for an introductory course in information theory." - Ximing Wu, American Journal of Agricultural Economics
IllustratedYes
Dewey Decimal519.54
Table Of ContentDedicationAcknowledgementsChapter 1 - Introduction Chapter 2 - Rational Inference: A Constrained Optimization FrameworkChapter 3 - The Metrics of Info-MetricsChapter 4 - Entropy MaximizationChapter 5 - Inference in The Real WorldChapter 6 - Advanced Inference in The Real WorldChapter 7: Efficiency, Sufficiency, and OptimalityChapter 8 - Prior InformationChapter 9 - A Complete Info-Metrics FrameworkChapter 10 - Modeling and TheoriesChapter 11 - Causal Inference via Constraint SatisfactionChapter 12 - Info-Metrics and Statistical Inference: Discrete ProblemsChapter 13 - Info-Metrics and Statistical Inference: Continuous ProblemsChapter 14 - New Applications Across DisciplinesEpilogueAppendicesList of SymbolsReferencesIndex
SynopsisFoundations of Info-Metrics provides an overview of modeling and inference, rather than a problem specific model, and progresses from the simple premise that information is often insufficient to provide a unique answer for decisions we wish to make. Each decision, or solution, is derived from the available input information along with a choice of inferential procedure., Info-metrics is the science of modeling, reasoning, and drawing inferences under conditions of noisy and insufficient information. It is at the intersection of information theory, statistical inference, and decision-making under uncertainty. It plays an important role in helping make informed decisions even when there is inadequate or incomplete information because it provides a framework to process available information with minimal reliance on assumptions thatcannot be validated.In this pioneering book, Amos Golan, a leader in info-metrics, focuses on unifying information processing, modeling and inference within a single constrainedoptimization framework. Foundations of Info-Metrics provides an overview of modeling and inference, rather than a problem specific model, and progresses from the simple premise that information is often insufficient to provide a unique answer for decisions we wish to make. Each decision, or solution, is derived from the available input information along with a choice of inferential procedure. The book contains numerous multidisciplinary applications and casestudies, which demonstrate the simplicity and generality of the framework in real world settings. Examples include initial diagnosis at an emergency room, optimal dose decisions, election forecasting, network andinformation aggregation, weather pattern analyses, portfolio allocation, strategy inference for interacting entities, incorporation of prior information, option pricing, and modeling an interacting social system. Graphical representations illustrate how results can be visualized while exercises and problem sets facilitate extensions. This book is this designed to be accessible for researchers, graduate students, and practitioners across the disciplines., Info-metrics is the science of modeling, reasoning, and drawing inferences under conditions of noisy and insufficient information. It is at the intersection of information theory, statistical inference, and decision-making under uncertainty. It plays an important role in helping make informed decisions even when there is inadequate or incomplete information because it provides a framework to process available information with minimal reliance on assumptions that cannot be validated. In this pioneering book, Amos Golan, a leader in info-metrics, focuses on unifying information processing, modeling and inference within a single constrained optimization framework. Foundations of Info-Metrics provides an overview of modeling and inference, rather than a problem specific model, and progresses from the simple premise that information is often insufficient to provide a unique answer for decisions we wish to make. Each decision, or solution, is derived from the available input information along with a choice of inferential procedure. The book contains numerous multidisciplinary applications and case studies, which demonstrate the simplicity and generality of the framework in real world settings. Examples include initial diagnosis at an emergency room, optimal dose decisions, election forecasting, network and information aggregation, weather pattern analyses, portfolio allocation, strategy inference for interacting entities, incorporation of prior information, option pricing, and modeling an interacting social system. Graphical representations illustrate how results can be visualized while exercises and problem sets facilitate extensions. This book is this designed to be accessible for researchers, graduate students, and practitioners across the disciplines., Info-metrics is the science of modeling, reasoning, and drawing inferences under conditions of noisy and insufficient information. It is at the intersection of information theory, statistical inference, and decision-making under uncertainty. It plays an important role in helping make informed decisions even when there is inadequate or incomplete information because it provides a framework to process available information with minimal reliance on assumptions that cannot be validated.In this pioneering book, Amos Golan, a leader in info-metrics, focuses on unifying information processing, modeling and inference within a single constrained optimization framework. Foundations of Info-Metrics provides an overview of modeling and inference, rather than a problem specific model, and progresses from the simple premise that information is often insufficient to provide a unique answer for decisions we wish to make. Each decision, or solution, is derived from the available input information along with a choice of inferential procedure. The book contains numerous multidisciplinary applications and case studies, which demonstrate the simplicity and generality of the framework in real world settings. Examples include initial diagnosis at an emergency room, optimal dose decisions, election forecasting, network and information aggregation, weather pattern analyses, portfolio allocation, strategy inference for interacting entities, incorporation of prior information, option pricing, and modeling an interacting social system. Graphical representations illustrate how results can be visualized while exercises and problem sets facilitate extensions. This book is this designed to be accessible for researchers, graduate students, and practitioners across the disciplines.
LC Classification NumberT50.G64 2017
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