9 edition of Maximum entropy econometrics found in the catalog.
Includes bibliographical references and index.
|Statement||Amos Golan, George Judge, Douglas Miller.|
|Series||Series in financial economics and quantitative analysis|
|Contributions||Judge, George G., Miller, Douglas.|
|LC Classifications||HB139 .J795 1996|
|The Physical Object|
|Pagination||xvi, 307 p. :|
|Number of Pages||307|
|LC Control Number||95041281|
Econometrics Vol. 2, Nos. 1–2 () 1– c A. Golan DOI: / Information and Entropy Econometrics — A Review and Synthesis∗ Amos Golan Department of Economics, American University, Massachusetts Avenue, NW Washington, DC , USA, [email protected] This work is dedicated to Marge and George Judge Abstract. Here, we present one version based in information theory, i.e., the Maximum Entropy Theory of Ecology (METE), which was introduced by Harte et al. [66,67], but called METE in the book, discussed in [68,69,70], and recently revisited to clarify some of the notation and incomplete : Rodrigo Cofré, Rubén Herzog, Derek Corcoran, Fernando E. Rosas.
A. Golan, " Information and Entropy Econometrics—A Review and Synthesis," Foundations and Trends® in Econometrics: Vol. 2: No 1–2, pp (A printed and bound version of this article is available at a 50% discount from Now Publishers. This can be obtained by Occupation: Professor. 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 Cited by:
Entropy econometrics developed by Golan, Judge and Miller () offers a useful approach for improving the assumptions made about parameters in economic models. As a starting point, it takes prior information whether from previous studies, theory, or — educated guesses — in the form of a probability distribution. Entropy econometrics then. In essence, this entropy econometrics approach constitutes a junction of two distinct concepts: Jayne’s maximum entropy principle and the Bayesian generalized method of moments. Rival econometric techniques are not conceptually adapted to solving complex inverse problems or are seriously limited when it comes to practical implementation.
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Maximum Entropy Econometrics will be of interest to econometricianstrying to devise procedures for recovering information from partialor incomplete data, as well as quantitative economists in financeand business, statisticians, and students and applied researchersin econometrics, engineering and the physical by: Maximum Entropy Econometrics will be of interest to econometricianstrying to devise procedures for recovering information from partialor incomplete data, as well as quantitative economists in financeand business, statisticians, and students and applied researchersin econometrics, engineering and the physical sciences.
Maximum Entropy Econometrics will be of interest to econometricianstrying to devise procedures for recovering information from partialor incomplete data, as well as quantitative economists in financeand business, statisticians, and students and applied researchersin econometrics, engineering and the physical : $ Applying Maximum Entropy to Econometric Problems (Advances in Econometrics) (Advances in Econometrics): Economics Books @ mat: Hardcover.
Maximum Entropy Econometrics will be of interest to econometricians trying to devise procedures for recovering information from partial or incomplete data, as well as quantitative economists in. In theoretical terms, the approach generalizes Gibbs-Shannon-Golan entropy models, which are useful for describing ergodic phenomena.
In essence, this entropy econometrics approach constitutes a junction of two distinct concepts: Jayne's maximum entropy principle and the Bayesian generalized method of moments.
Maximum entropy econometrics robust estimation with limited data by Amos Golan. Published by Wiley in Chichester [England], New York. Written in EnglishPages: Maximum entropy econometrics: robust estimation with limited data. Summary: This book offers solutions to the problems commonly encountered by economists trying to squeeze information out of partial or incomplete data--which is usually what they have to work with.
Golan, Amos & Judge, George G. & Miller, Douglas, "Maximum Entropy Econometrics," Staff General Research Papers ArchiveIowa State University, Department. Maximum Entropy Econometrics. Amos Golan (), George G. Judge and Douglas Miller. Staff General Research Papers Archive from Iowa State University, Department of Economics.
Date: References: Add references at CitEc Citations: View citations in EconPapers () Track citations by RSS feed There are no downloads for this item, see the EconPapers FAQ for hints about obtaining by: This volume has its origin in the Fifth, Sixth and Seventh Workshops on and Bayesian Methods in Applied Statistics", held at "Maximum-Entropy the University of Wyoming, August, and at Seattle University, August, and AugustIt was anticipated that the proceedings of.
Maximum entropy econometrics: robust estimation with limited data. Responsibility George Judge, Amos Golan and Douglas Miller. The Classical Maximum Entropy Formalism: A Review. PURE INVERSE PROBLEMS. This book offers solutions to the problems commonly encountered by economists trying to squeeze information out of partial or incomplete.
Description: This book is a collection of introductory, interdisciplinary articles and lectures covering the fundamentals of the maximum entropy approach, a powerful new technique that provides a much needed extension of the established principles of rational inference in the sciences.
Maximum entropy allows the interpretation of incomplete and "noisy" data, providing a description of the underlying. 图书Maximum Entropy Econometrics 介绍、书评、论坛及推荐. Maximum Entropy Economeirics provides a new basis for learning from economic and statistical models that may be non-regular in the sense that they are ill-posed or underdetermined and the data are partial or incomplete.
By extending the maximum entropy formalisms used in. Maximum Entropy Econometrics: Robust Estimation with Limited Data (Financial Economics and Quantitative Analysis Series) by George JudgeR.e.a.d and D.o.w.n.l.o.a.d N.
This Is The First Comprehensive Book About Maximum Entropy Principle And Its Applications To A Diversity Of Fields Like Statistical Mechanics, Thermo-Dynamics, Business, Economics, Insurance, Finance, Contingency Tables, Characterisation Of Probability Distributions (Univariate As Well As Multivariate, Discrete As Well As Continuous), Statistical Inference, Non-Linear Spectral Analysis Of.
He has published in economics, econometrics, statistics, mathematics, physics and philosophy journals. His books include Maximum Entropy Econometrics: Robust Estimation with Limited Data (coauthored with Judge and Miller) and Information and Entropy Econometrics - A.
The eminent physicist Ed. Jaynes (a) wrote: "Information theory provides a constructive criterion for setting up probability distributions on the basis of partial knowledge, and leads to a type of statistical inference which is called the maximum entropy estimate.
- Maximum Entropy Econometrics: Robust Estimation with Limited Data by Golan, Amos; Judge, George G ; Miller, Douglas, Used You Searched For: ISBN: The 10th International Workshop on Maximum Entropy and Bayesian Methods, Max was held in Laramie, Wyoming from 30 July to 3 August This volume contains the scientific presentations given at that meeting.
This series of workshops originated in Laramie inwhere the first three of. In this paper, we suggest a general density function based on the maximum entropy (ME) approach that takes account of asymmetry, excess kurtosis and also of high peakedness.
The ME principle is based on the efficient use of available information, and as is well known, many of the standard family of distributions can be derived from the ME by: This is typically treated in economics by introducing marginal utility as a Lagrange multiplier. Jumping off from Gary Becker’s paper "Irrational Behavior and Economic Theory" — a maximum entropy argument in disguise — we introduce Peter Fielitz and Guenter Borchardt’s concept of "information equilibrium" presented in arXiv Author: Jason Smith.Soil depth plays an important role in landslide disaster prevention and is a key factor in slopeland development and management.
Existing soil depth maps are outdated and incomplete in Taiwan. There is a need to improve the accuracy of the map. The Kriging method, one of the most frequently adopted estimation approaches for soil depth, has room for accuracy improvements.
An appropriate soil Cited by: 1.