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Informational complexity criteria for regression models

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  • Bozdogan, Hamparsum
  • Haughton, Dominique M. A.

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  • Bozdogan, Hamparsum & Haughton, Dominique M. A., 1998. "Informational complexity criteria for regression models," Computational Statistics & Data Analysis, Elsevier, vol. 28(1), pages 51-76, July.
  • Handle: RePEc:eee:csdana:v:28:y:1998:i:1:p:51-76
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    References listed on IDEAS

    as
    1. Bearse, Peter M & Bozdogan, Hamparsum & Schlottmann, Alan M, 1997. "Empirical Econometric Modelling of Food Consumption Using a New Informational Complexity Approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(5), pages 563-586, Sept.-Oct.
    2. Hamparsum Bozdogan, 1987. "Model selection and Akaike's Information Criterion (AIC): The general theory and its analytical extensions," Psychometrika, Springer;The Psychometric Society, vol. 52(3), pages 345-370, September.
    3. Bearse, Peter M & Bozdogan, Hamparsum & Schlottmann, Alan M, 1997. "Empirical Econometric Modelling of Food Consumption Using a New Informational Complexity Approach: Reply," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(5), pages 590-592, Sept.-Oct.
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    Cited by:

    1. Eylem Deniz & Oguz Akbilgic & J. Andrew Howe, 2011. "Model selection using information criteria under a new estimation method: least squares ratio," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(9), pages 2043-2050, November.
    2. Magnus, Jan R., 2007. "The Asymptotic Variance Of The Pseudo Maximum Likelihood Estimator," Econometric Theory, Cambridge University Press, vol. 23(5), pages 1022-1032, October.
    3. Alexander Gorobets, 2005. "The Optimal Prediction Simultaneous Equations Selection," Economics Bulletin, AccessEcon, vol. 3(36), pages 1-8.
    4. repec:ebl:ecbull:v:3:y:2005:i:36:p:1-8 is not listed on IDEAS
    5. Gorobets, A., 2004. "The Optimal Prediction Simultaneous Equations Selection," ERIM Report Series Research in Management ERS-2003-023-ORG, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    6. Edwards, Richard E. & New, Joshua & Parker, Lynne E. & Cui, Borui & Dong, Jin, 2017. "Constructing large scale surrogate models from big data and artificial intelligence," Applied Energy, Elsevier, vol. 202(C), pages 685-699.

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