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A Program for Box-Cox Transformation in Regression Models with Heteroskedastic and Autoregressive Residuals

Author

Listed:
  • Liem, T.C.
  • Gaudry, M.
  • Dagenais, M.G.

Abstract

L-1.2 Is a Program Designed to Deal with the Specification of the Functional Form in the Generalized Single-Equation Regression Model When the Functional Form of Heteroskedasticity of the Residuals, Which May Also Be Autocorrelated, Is Fully Analysed. Fixed Or Estimated Parameters in the Box-Cox Transformations Can Be Associated with the Dependent and Groups of Independent Variables, Which May Be Simultaneously Modified by a Chosen Autocorrelation Structure in Which the Autoregressive Parameters Are Estimated, and by a Selected Functional Form of Heteroskedasticity in Which Covariance Matrix of All Parameter Estimates of the System Is Computed. a Number of Useful Outputs, Including Elaborate Statistics Associated with Forecasts and Plots of the Likelihood Functions, Can Also Be Obtained.

Suggested Citation

  • Liem, T.C. & Gaudry, M. & Dagenais, M.G., 1987. "A Program for Box-Cox Transformation in Regression Models with Heteroskedastic and Autoregressive Residuals," Cahiers de recherche 8714, Universite de Montreal, Departement de sciences economiques.
    • Handle: RePEc:mtl:montde:8714
    as

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