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Uncertainty Analysis in Econometrics with Applications

Uncertainty Analysis in Econometrics with Applications Proceedings of the Sixth International Conference of the Thailand Econometric Society TES'2013 / [electronic resource] : edited by Van-Nam Huynh, Vladik Kreinovich, Songsak Sriboonchitta, Komsan Suriya. - XVI, 319 p. 34 illus. online resource. - Advances in Intelligent Systems and Computing, 200 2194-5357 ; . - Advances in Intelligent Systems and Computing, 200 .

Part I Keynote Addresses -- Part II Fundamental Theory -- Part III Applications.

Unlike uncertain dynamical systems in physical sciences where models for prediction are somewhat given to us by physical laws, uncertain dynamical systems in economics need statistical models. In this context, modeling and optimization surface as basic ingredients for fruitful applications. This volume concentrates on the current methodology of copulas and maximum entropy optimization. This volume contains main research presentations at the Sixth International Conference of the Thailand Econometrics Society held at the Faculty of Economics, Chiang Mai University, Thailand, during January 10-11, 2013. It consists of keynote addresses, theoretical and applied contributions. These contributions to Econometrics are somewhat centered around the theme of Copulas and Maximum Entropy Econometrics. The method of copulas is applied to a variety of economic problems where multivariate model building and correlation analysis are needed. As for the art of choosing copulas in practical problems, the principle of maximum entropy surfaces as a potential way to do so. The state-of-the-art of Maximum Entropy Econometrics is presented in the first keynote address, while the second keynote address focusses on testing stationarity in economic time series data.

9783642354434

10.1007/978-3-642-35443-4 doi


Engineering.
Artificial intelligence.
Computational intelligence.
Econometrics.
Engineering.
Computational Intelligence.
Artificial Intelligence (incl. Robotics).
Econometrics.

Q342

006.3