Ridge regression methodology in partial linear models with correlated errors

References

• Wahba , G. 1990 . “ Spline models for observational data ” . In CBMS-NSF Regional Conference Series in Applied Mathematics , Vol. 59 , Philadelphia : SIAM .
   Google Scholar
• Hastie , T. and Tibshirani , R. J. 1990 . Generalized Additive Models , London, New York : Chapman and Hall .
   Google Scholar
• Ruppert , D. , Wand , M. P. , Holst , U. and Hssjer , O. 1997 . Local polynomial variance-function estimation . Technometrics , 39 : 262 – 272 .
   Web of Science ®Google Scholar
• Ahn , H. and Powell , J. 1993 . Semiparametric estimation of censored selection models with a nonparametric selection mechanism . J. Econ. , 58 : 3 – 29 .
   Web of Science ®Google Scholar
• L. Wang, L.D. Brown, and T.T. Cai, A difference based approach to semiparametric partial linear model, Tech. Rep., Department of Statistics, The Wharton School, University of Pennsylvania, 2007
   Google Scholar
• Hoerl , A. E. and Kennard , R. W. 1970 . Ridge regression biased estimation for nonorthogonal problems . Technometrics , 12 : 69 – 82 .
   Web of Science ®Google Scholar
• Varian , H. R. 1975 . “ A Bayesian approach to real estate assessment ” . In Studies in Bayesian Econometrics and Statistics in Honor of Leonard J. Savage , Edited by: Fienberg , S. E. and Zellner , A. 195 – 208 . Amsterdam : North-Holland .
   Google Scholar
• Zellner , A. 1986 . Bayesian estimation and prediction using asymmetric loss functions . J. Am. Stat. Assoc. , 81 : 446 – 451 .
   Web of Science ®Google Scholar
• Zellner , A. 1994 . “ Bayesian and non-Bayesian estimation using balanced loss function ” . In Statistical Decision Theory and Related Topics , Edited by: Gupta , S. S. and Berger , J. O. 377 – 390 . Berlin : Springer Verlag .
   Google Scholar
• Giles , J. A. , Giles , D. E.A. and Oktani , K. 1996 . The exact risk of some pre-test and Stein-type regression estimators under balanced loss . Commun. Stat. Theory Methods , 25 : 2901 – 2929 .
   Web of Science ®Google Scholar
• Ohtani , K. , Giles , D. E.A. and Giles , J. A. 1997 . The exact risk performance of a pre-test estimator in a heteroskedastic linear regression model under the balanced loss function . Econ. Rev. , 16 : 119 – 133 .
   Google Scholar
• Dey , D. K. , Ghosh , M. and Strawderman , W. E. 1999 . On estimation with balanced loss function . Stat. Probab. Lett. , 45 : 97 – 101 .
   Web of Science ®Google Scholar
• Chung , Y. , Kim , C. and Dey , D. K. 1999 . A new class of minimax estimators of multivariate normal mean vectors under balanced loss function . Stat. Decis. , 17 ( 3 ) : 255 – 266 .
   Google Scholar
• Shalabh . 2001 . Least squares estimators in measurement error models under the balanced loss function . Test , 10 : 301 – 308 .
   Web of Science ®Google Scholar
• Wan , A. T.K. 2002 . On generalized ridge regression estimators under collinearity and balanced loss . Appl. Math. Comput. , 129 : 455 – 467 .
   Web of Science ®Google Scholar
• Tothenberg , H. and Shalabh . 2005 . Estimation of regression coefficients subject to exact linear restrictions when some observations are missing and quadratic error balanced loss function is used . Test , 14 : 385 – 396 .
   Web of Science ®Google Scholar
• Swamy , P. A.V.B. , Mehta , J. S. and Rappoport , P. N. 1978 . Two methods of evaluating Hoerl and Kennard's ridge regression . Commun. Statist. , 12 : 1133 – 1155 .
   Google Scholar
• Sarkar , N. 1992 . A new estimator combining the ridge regression and the restricted least squares methods of estimation . Commun. Stat. Theory Methods , 21 : 1987 – 2000 .
   Web of Science ®Google Scholar
• Grob , J. 2003 . Restricted ridge estimation . Stat. Probab. Lett. , 65 : 57 – 64 .
   Web of Science ®Google Scholar
• Kibria , B. M.G. and Saleh , A. K.Md.E. 2004 . Preliminary test ridge regression estimators with students t errors and conicting test-statistics . Metrika , 59 : 105 – 124 .
   Web of Science ®Google Scholar
• Zhong , Z. and Yang , H. 2007 . Ridge estimation to the restricted linear model . Commun. Stat. Theory Methods , 36 : 2099 – 2115 .
   Web of Science ®Google Scholar
• Zhang , C. and Yang , H. 2007 . The conditional ridge-type estimation in singular linear model with linear equality restriction . Statistics , 41 ( 6 ) : 485 – 494 .
   Web of Science ®Google Scholar
• Tabakan , G. and Akdeniz , F. 2008 . Difference-based ridge estimator of parameters in partial linear model . Stat. Pap. , (in press)
   Google Scholar
• Akdeniz , F. and Tabakan , G. 2009 . Restricted ridge estimators of the parameters in semiparametric regression model . Commun. Stat. Theory Methods , 38 ( 11 ) : 1852 – 1869 .
   Web of Science ®Google Scholar
• Yatchew , A. 1997 . An elementary estimator of the partial linear model . Econ. Lett. , 57 : 135 – 143 .
   Web of Science ®Google Scholar
• Yatchew , A. 2003 . Semiparametric Regression for the Applied Econometrican , Cambridge : Cambridge University press .
   Google Scholar
• Yatchew , A. 2000 . Scale economies in electricity distribution: A semiparametric Analysis . J. Appl. Econ. , 57 : 187 – 210 .
   Web of Science ®Google Scholar
• Swamy , P. A.V.B. and Mehta , J. S. 1977 . A note on minimum average risk estimator for coefficient in linear models . Commun. Statist. , 6 : 1161 – 1186 .
   Google Scholar
• Hall , P. , Kay , J. W. and Titterington , D. M. 1990 . On estimation of noise variance in two-dimensional signal processing . Adv. Appl. Probab. , 23 : 476 – 495 .
   Web of Science ®Google Scholar