Modified Ridge Parameters for Seemingly Unrelated Regression Model

References

• Alkhamisi , M. A. , Shukur , G. ( 2008 ). Developing ridge parameters for SUR model . Commun. Statist. Theor. Meth. 37 ( 4 ): 544 – 564 .
   Web of Science ®Google Scholar
• Alkhamisi , M. A. , Khalaf , G. , Shukur , G. ( 2006 ). Some modifications for choosing ridge parameter . Commun. Statist. Theor. Meth. 35 : 1 – 16 .
   Web of Science ®Google Scholar
• Brown , P. J. , Zidek , J. V. ( 1980 ). Adaptive multivariate ridge regression . Ann. Statist. 8 ( 1 ): 64 – 74 .
   Web of Science ®Google Scholar
• Chib , S. , Greenberg , E. ( 1995 ). Hierarchical analysis of SUR model with extensions to correlated serial errors and time varying parameter models . J. Econometrics 68 : 339 – 360 .
   Web of Science ®Google Scholar
• Fiebig , G. D. , Kim , H. J. ( 2000 ). Estimation and inference in SUR models when the number of equations is large . Econometric Rev. 19 ( 1 ): 105 – 130 .
   Google Scholar
• Firinguetti , L. ( 1997 ). Ridge regression in the context of a system of seemingly unrelated regression equations . J. Statist. Comput. Simul. 56 : 145 – 162 .
   Web of Science ®Google Scholar
• Frisch , R. (1934). Statistical confluence analysis by means of complete regression systems. Publication 5. Oslo: University Institute of Economics.
   Google Scholar
• Gruber , M. H. J. ( 1998 ). Improving Efficiency by Shrinkage: The James-Stein and Ridge Regression Estimators . New York : Marcel Dekker .
   Google Scholar
• Gruber , M. H. J. ( 2010 ). Regression Estimators A Comparative Study. , 2nd ed. Baltimore , MD : Johns Hopkins University Press .
   Google Scholar
• Haitovsky , Y. ( 1987 ). On multivariate ridge regression . Biometrika 74 : 563 – 70 .
   Web of Science ®Google Scholar
• Hoerl , A. E. , Kennard , R. W. ( 1970a ). Ridge regression: Biased estimation for non-orthogonal problems . Technometrics 12 : 55 – 67 .
   Web of Science ®Google Scholar
• Hoerl , A. E. , Kennard , R. W. ( 1970b ). Ridge regression: Application to non-orthogonal problems . Technometrics 12 : 69 – 82 .
   Web of Science ®Google Scholar
• Hoerl , A. E. , Kennard , R. W. , Baldwin , K. F. ( 1975 ). Ridge regression – some simulations . Commun. Statist. B 4 : 105 – 123 .
   Google Scholar
• Khalaf , G. , Shukur , G. ( 2005 ). Choosing ridge parameters for regression problems . Commun. Statist. Theor. Meth. 34 : 1177 – 1182 .
   Web of Science ®Google Scholar
• Kibria , B. M. G. ( 2003 ). Performance of some new ridge regression estimators . Commun. Statist. B 2 ( 32 ): 419 – 435 .
   Google Scholar
• Koop , G. ( 2003 ). Bayesian Econometrics. John Wiley & Sons .
   Google Scholar
• Muniz , G. , Kibria , B. M. G. ( 2009 ). On some ridge regression estimators: An empirical comparisons . Commun. Statist. Simul. Computat. 38 ( 3 ): 621 – 630 .
   Web of Science ®Google Scholar
• Saleh , A. K. Md. E. , Kibiria , B. M. G. ( 1993 ). Performance of some new preliminary test ridge regression estimators and their properties . Common. Statist. A 22 : 2747 – 2764 .
   Web of Science ®Google Scholar
• Srivastava , V. , Giles , D. ( 1987 ). Seemingly Unrelated Regression Equations Models . New York : Marcel Dekker .
   Google Scholar
• Vinod , H. D. ( 1978 ). A survey of ridge regression and related techniques for improvements over ordinary least squares . Reu. Econ. Stat. 60 : 121 – 131 .
   Web of Science ®Google Scholar
• Zellner , A. ( 1962 ). An Efficient method of estimating seemingly unrelated regressions and tests for aggregation bias . J. Am. Statist. Assoc. 57 : 348 – 368 .
   Web of Science ®Google Scholar