Information and Entropy Econometrics
Information and Entropy Econometrics

Author: Amos Golan

Publisher: Now Publishers Inc

Published: 2008

Total Pages: 167

ISBN-13: 160198104X

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Information and Entropy Econometrics - A Review and Synthesis summarizes the basics of information theoretic methods in econometrics and the connecting theme among these methods. The sub-class of methods that treat the observed sample moments as stochastic is discussed in greater details. I Information and Entropy Econometrics - A Review and Synthesis -focuses on inter-connection between information theory, estimation and inference. -provides a detailed survey of information theoretic concepts and quantities used within econometrics and then show how these quantities are used within IEE. -pays special attention for the interpretation of these quantities and for describing the relationships between information theoretic estimators and traditional estimators. Readers need a basic knowledge of econometrics, but do not need prior knowledge of information theory. The survey is self contained and interested readers can replicate all results and examples provided. Whenever necessary the readers are referred to the relevant literature. Information and Entropy Econometrics - A Review and Synthesis will benefit researchers looking for a concise introduction to the basics of IEE and to acquire the basic tools necessary for using and understanding these methods. Applied researchers can use the book to learn improved new methods, and applications for extracting information from noisy and limited data and for learning from these data.

Maximum Entropy Econometrics
Maximum Entropy Econometrics

Author: Amos Golan

Publisher: John Wiley & Sons

Published: 1996-05

Total Pages: 336

ISBN-13:

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This monograph examines the problem of recovering and processing information when the underlying data are limited or partial, and the corresponding models that form the basis for estimation and inference are ill-posed or undermined

Formal Theories of Information
Formal Theories of Information

Author: Giovanni Sommaruga

Publisher: Springer Science & Business Media

Published: 2009-04-22

Total Pages: 275

ISBN-13: 3642006582

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This book presents the scientific outcome of a joint effort of the computer science departments of the universities of Berne, Fribourg and Neuchâtel. Within an initiative devoted to "Information and Knowledge", these research groups collaborated over several years on issues of logic, probability, inference, and deduction. The goal of this volume is to examine whether there is any common ground between the different approaches to the concept of information. The structure of this book could be represented by a circular model, with an innermost syntactical circle, comprising statistical and algorithmic approaches; a second, larger circle, the semantical one, in which "meaning" enters the stage; and finally an outermost circle, the pragmatic one, casting light on real-life logical reasoning. These articles are complemented by two philosophical contributions exploring the wide conceptual field as well as taking stock of the articles on the various formal theories of information.

Maximum Entropy and Bayesian Methods Garching, Germany 1998
Maximum Entropy and Bayesian Methods Garching, Germany 1998

Author: Wolfgang von der Linden

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 380

ISBN-13: 9401147108

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In 1978 Edwin T. Jaynes and Myron Tribus initiated a series of workshops to exchange ideas and recent developments in technical aspects and applications of Bayesian probability theory. The first workshop was held at the University of Wyoming in 1981 organized by C.R. Smith and W.T. Grandy. Due to its success, the workshop was held annually during the last 18 years. Over the years, the emphasis of the workshop shifted gradually from fundamental concepts of Bayesian probability theory to increasingly realistic and challenging applications. The 18th international workshop on Maximum Entropy and Bayesian Methods was held in Garching / Munich (Germany) (27-31. July 1998). Opening lectures by G. Larry Bretthorst and by Myron Tribus were dedicated to one of th the pioneers of Bayesian probability theory who died on the 30 of April 1998: Edwin Thompson Jaynes. Jaynes revealed and advocated the correct meaning of 'probability' as the state of knowledge rather than a physical property. This inter pretation allowed him to unravel longstanding mysteries and paradoxes. Bayesian probability theory, "the logic of science" - as E.T. Jaynes called it - provides the framework to make the best possible scientific inference given all available exper imental and theoretical information. We gratefully acknowledge the efforts of Tribus and Bretthorst in commemorating the outstanding contributions of E.T. Jaynes to the development of probability theory.

Generalized Statistical Thermodynamics
Generalized Statistical Thermodynamics

Author: Themis Matsoukas

Publisher: Springer

Published: 2019-05-08

Total Pages: 373

ISBN-13: 3030041492

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This book gives the definitive mathematical answer to what thermodynamics really is: a variational calculus applied to probability distributions. Extending Gibbs's notion of ensemble, the Author imagines the ensemble of all possible probability distributions and assigns probabilities to them by selection rules that are fairly general. The calculus of the most probable distribution in the ensemble produces the entire network of mathematical relationships we recognize as thermodynamics. The first part of the book develops the theory for discrete and continuous distributions while the second part applies this thermodynamic calculus to problems in population balance theory and shows how the emergence of a giant component in aggregation, and the shattering transition in fragmentation may be treated as formal phase transitions. While the book is intended as a research monograph, the material is self-contained and the style sufficiently tutorial to be accessible for self-paced study by an advanced graduate student in such fields as physics, chemistry, and engineering.

Universal Estimation of Information Measures for Analog Sources
Universal Estimation of Information Measures for Analog Sources

Author: Qing Wang

Publisher: Now Publishers Inc

Published: 2009-05-26

Total Pages: 104

ISBN-13: 1601982305

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Entropy, mutual information and divergence measure the randomness, dependence and dissimilarity, respectively, of random objects. In addition to their prominent role in information theory, they have found numerous applications, among others, in probability theory statistics, physics, chemistry, molecular biology, ecology, bioinformatics, neuroscience, machine learning, linguistics, and finance. Many of these applications require a universal estimate of information measures which does not assume knowledge of the statistical properties of the observed data. Over the past few decades, several nonparametric algorithms have been proposed to estimate information measures. Universal Estimation of Information Measures for Analog Sources presents a comprehensive survey of universal estimation of information measures for memoryless analog (real-valued or real vector-valued) sources with an emphasis on the estimation of mutual information and divergence and their applications. The book reviews the consistency of the universal algorithms and the corresponding sufficient conditions as well as their speed of convergence. Universal Estimation of Information Measures for Analog Sources provides a comprehensive review of an increasingly important topic in Information Theory. It will be of interest to students, practitioners and researchers working in Information Theory

Econometric Foundations Pack with CD-ROM
Econometric Foundations Pack with CD-ROM

Author: Ron Mittelhammer (Prof.)

Publisher: Cambridge University Press

Published: 2000-07-28

Total Pages: 794

ISBN-13: 9780521623940

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The text and accompanying CD-ROM develop step by step a modern approach to econometric problems. They are aimed at talented upper-level undergraduates, graduate students, and professionals wishing to acquaint themselves with the pinciples and procedures for information processing and recovery from samples of economic data. The text fully provides an operational understanding of a rich set of estimation and inference tools, including tradional likelihood based and non-traditional non-likelihood based procedures, that can be used in conjuction with the computer to address economic problems.

Econometrics of Information and Efficiency
Econometrics of Information and Efficiency

Author: Jati Sengupta

Publisher: Springer Science & Business Media

Published: 2013-03-14

Total Pages: 267

ISBN-13: 9401582025

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Econometrics as an applied discipline attempts to use information in a most efficient manner, yet the information theory and entropy approach developed by Shannon and others has not played much of a role in applied econometrics. Econometrics of Information and Efficiency bridges the gap. Broadly viewed, information theory analyzes the uncertainty of a given set of data and its probabilistic characteristics. Whereas the economic theory of information emphasizes the value of information to agents in a market, the entropy theory stresses the various aspects of imprecision of data and their interactions with the subjective decision processes. The tools of information theory, such as the maximum entropy principle, mutual information and the minimum discrepancy are useful in several areas of statistical inference, e.g., Bayesian estimation, expected maximum likelihood principle, the fuzzy statistical regression. This volume analyzes the applications of these tools of information theory to the most commonly used models in econometrics. The outstanding features of Econometrics of Information and Efficiency are: A critical survey of the uses of information theory in economics and econometrics; An integration of applied information theory and economic efficiency analysis; The development of a new economic hypothesis relating information theory to economic growth models; New lines of research are emphasized.

Advances in Info-Metrics
Advances in Info-Metrics

Author: Min Chen

Publisher: Oxford University Press, USA

Published: 2020

Total Pages: 557

ISBN-13: 0190636688

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"Info-metrics is a framework for rational inference on the basis of limited, or insufficient, information. It is the science of modeling, reasoning, and drawing inferences under conditions of noisy and insufficient information. Info-metrics has its roots in information theory (Shannon, 1948), Bernoulli's and Laplace's principle of insufficient reason (Bernoulli, 1713) and its offspring the principle of maximum entropy (Jaynes, 1957). It is an interdisciplinary framework situated at the intersection of information theory, statistical inference, and decision-making under uncertainty. Within a constrained optimization setup, info-metrics provides a simple way for modeling and understanding all types of systems and problems. It is a framework for processing the available information with minimal reliance on assumptions and information that cannot be validated. Quite often a model cannot be validated with finite data. Examples include biological, social and behavioral models, as well as models of cognition and knowledge. The info-metrics framework extends naturally for tackling these types of common problems"--

The Theory of Epistemic Fields
The Theory of Epistemic Fields

Author: Kofi Kissi Dompere

Publisher: Springer Nature

Published: 2024

Total Pages: 581

ISBN-13: 3031424700

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The book is about the development of the theory of epistemic fields with the corresponding relational and information fields as a framework for the understanding of strategies and tactics of the theory of knowing as the production of intellectual investment flows and the theory of knowledge accumulation as the production of intellectual capital stocks in systems of factories and departments providing the foundations for the development of open algorithms in the open space of problem-solution dualities. The concepts and the roles of thinking and reasoning with curiosity, creativity, hope, Ill-posed problems, phantom problems, unsolved problems, misinformation, disinformation, fake news, and courage are introduced, defined, and analyzed on the cognitive journeys over the space of ignorance-knowledge dualities, where dualistic-polar conflicts between duals in the space of ignorance-knowledge dualities are resolved with the instruments of fuzzy optimization, the results of which are used to induced the zones of ignorance, the zones of knowledge, and the zones of contentions. A complete development of the set of connecting paths of spaces and sub-spaces is provided, where all varieties, categories, and spaces reside in dualistic-polar structures with knowledge stock viewed as a single tree with the same roots, one trunk, many branches, and a fruit cocktail. The ontological space contains the space of actual-potential dualities as the primary category of knowing, and the epistemological space contains the space of imagination-reality dualities as the derived category of knowing within the space of primary-derived dualities. The space of potentials contains the space of imaginations which contains the sub-spaces of possibility-impossibility, probability-improbability, and possibility-probability dualities with corresponding spaces of necessity-freedom and anticipation-expectation dualities leading to the conception of the possible-world-impossible-world dualities in the space of semantic-non-semantic dualities. This book is also a continuation of the sequence of my works on the theories of paradigms of thought, rationality, info-statics, info-dynamics, entropy, problem-solution dualities in self-contained mathematics and philosophy, and their relational connectivity to information, language, knowing, knowledge, cognitive practices and open maching learning relative to nominalism, and the space of construction-reduction dualities over the spaces of fundamental-applied, production-consumption, input-output, and cost-benefit dualities.