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by R. Carter Hill
Download Applying Maximum Entropy to Econometric Problems (Advances in Econometrics) (Advances in Econometrics) fb2
Business & Finance
  • Author:
    R. Carter Hill
  • ISBN:
    0762301872
  • ISBN13:
    978-0762301874
  • Genre:
  • Publisher:
    Emerald Group Publishing Limited (January 1, 1997)
  • Pages:
    376 pages
  • Subcategory:
    Business & Finance
  • Language:
  • FB2 format
    1207 kb
  • ePUB format
    1341 kb
  • DJVU format
    1208 kb
  • Rating:
    4.6
  • Votes:
    515
  • Formats:
    lrf docx txt mbr


Advances in Econometrics publishes original scholarly econometrics papers with the intention of expanding the use of developed and emerging econometric techniques by disseminating ideas on the theory and practice of econometrics throughout the empirical economic, business.

Advances in Econometrics publishes original scholarly econometrics papers with the intention of expanding the use of developed and emerging econometric techniques by disseminating ideas on the theory and practice of econometrics throughout the empirical economic, business and social science literature.

Applying Maximum Entrophy to Econometric Problems Vol 1.

Shipped in 8 to 10 working days. This volume of Advances in Econometrics looks at applying maximum entropy to econometric problems and consists of two sections: the first section contains papers developing econometric methods based on the entropy principle; an interesting array of applications is presented in the second section of the volume. The entropy concept was developed and used by Shannon in 1940 as a measure of uncertainty in the context of information theory.

Start by marking Advances in Econometrics, Volume 12: Applying . Papers in this volume discuss new econometric tec Often applied econometricians are faced with working with data that is less than ideal.

Start by marking Advances in Econometrics, Volume 12: Applying Maximum Entropy to Econometric Problems as Want to Read: Want to Read savin. ant to Read. Papers in this volume discuss new econometric techniques for addressing these problems.

Economic inequality: Innovations in quantitative economics: Nonparametric and robust inference. Bayesian computational methods. Applying maximum entropy to econometric problems. Co-integration, spurious regressions and unit roots.

Advances in Econometrics aims to annually publish original scholarly . Volume 12: Applying Maximum Entropy to Econometric Problems.

Advances in Econometrics aims to annually publish original scholarly econometrics papers on designated topics with the intention of expanding the use of developed and emerging econometric techniques by disseminating ideas on the theory and practice of econometrics throughout the empirical economic, business and social science literature.

Advances in Econometrics, Income Distribution and Scientific Methodology. Fomby, T. B. and R. C. Hill (1997) Advances in Econometrics: Applying Maximum Entropy to Econometric Problems, Vol. 12, Greenwich CT: JAI Press. Advances in Econometrics, Income Distribution and Scientific Methodology pp 61-77 Cite as. Measuring Informativeness of Data by Entropy and Variance. 1983) Information Measures and Bayesian Hierarchical Models, Journal of the American Statistical Association, 78, 408 - 41. rossRefGoogle Scholar.

Advances in Econometrics. Book · January 2000 with 14 Reads. Influences determining the progress of econometrics are analysed and their possible future impacts conjectured. How we measure 'reads'. One way to tackle this problem is to introduce a linear loss function over the errors and a penalty on the magnitude of model coefficients. This leads to qualities such as robustness to outliers and avoidance of the problem of over¯tting.

Carter Hill ed: Advances in Econometrics - Applying Maximum Entropy to Econometric Problems, vol. 12, Jai Press In. London, 1997. Stuzer, M. Entropy, 2, (2000), 70-77. Zellner, A. Journal of Econometrics, 75, (1996), 51-68. entropy normal entropy.

Chapter 1 An Introduction to Econometrics. Principles of Econometrics. Chapter 2 The Simple Linear Regression Model. Louisiana State University. It is assumed that students have taken courses in the principles of economics, and elementary statistics.

Introductory Econometrics Wooldridge, Jeffrey M. Principles of Econometrics Hill, R. Carter. This volume consists of two sections. The first section contains papers developing econometric methods based on the entropy principle. An interesting array of applications is presented in the second section of the volume.

The entropy concept was developed and used by Shannon in 1940 as a measure of uncertainty in the context of information theory. In 1957 Jaynes made use of Shannon's entropy concept as a basis for estimation and inference in problems that are ill-suited for traditional statistical procedures. This volume consists of two sections. The first section contains papers developing econometric methods based on the entropy principle. An interesting array of applications is presented in the second section of the volume.