Feasible Generalized Stein-Rule Restricted Ridge Regression Estimators

Aitken, A.C. (1935). On Least Squares and Linear Combinations of Observations.Proc. Roy. Soc. Edinburgh Sect. A. 55: 42-48.Search in Google Scholar

Chaturvedi, A., Shukla, G. (1990). Stein Rule Estimation in Linear Model with Non-Scalar Error Covariance Matrix.Sankhya B. 52: 293-304.Search in Google Scholar

Chaturvedi, A., Van Hoa, T. and Shukla, G. (1996).Improved Estimation in the Restricted Regression Model with Non-Spherical Disturbances.J. Quant. Econ. 12: 115-123.Search in Google Scholar

Chaturvedi, A., Wan, A.T.K. and Singh, S.P. (2001).Stein-Rule Restricted Regression Estimator in a Linear Regression Model with Nonspherical Disturbances.Comm. Statist. Theory Methods. 30 (1): 55-68.Search in Google Scholar

Chaturvedi, A., Shalabh, S. (2014). Bayesian Estimation of Regression Coefficients Under Extended Balanced Loss Function. Commun.Stat. Theory Methods. 43: 4253-4264.Search in Google Scholar

Eledum, H., Zahri, M. (2013).Relaxation Method for Two Stages Ridge Regression Estimator.Int. J. Pure Appl. Math. Sci. 85 (4): 653-667.Search in Google Scholar

Groß J. (2003). Restricted Ridge Estimation.Statist.Probab.Lett. 65: 57-64.Search in Google Scholar

Güler, H., Kaçıranlar, S. (2009). A Comparison of Mixed and Ridge Estimators of Linear Models.Comm. Statist. Simulation Comput. 38 (2): 368-401.Search in Google Scholar

Hoerl, E., Kennard, R. W. (1970a). Ridge Regression: Biased Estimation for Nonorthogonal Problems. Technometrics 12 (1): 55-67.10.1080/00401706.1970.10488634Search in Google Scholar

Hoerl, A.E., Kennard, R.W. and Baldwin, K.F. (1975). Ridge Regression: Some Simulations. Comm. Statist. Simulation Comput. 4: 105-123.Search in Google Scholar

James, W., Stein, C. (1960).Estimation with Quadratic Loss.Proc. Fourth Berkeley Symp.on Math. Statist.and Prob., Vol. 1, Univ. of Calif. Press, 361-379, Berkeley.Search in Google Scholar

Kaçıranlar, S., Sakallıoğlu, S., Özkale, M.R. and Güler, H. (2011). More On the Restricted Ridge Regression Estimation. J. Stat. Comput. Simul. 81 (11): 1433-1448.Search in Google Scholar

Kibria, B.M.G. (2003). Performance of Some New Ridge Regression Estimators.Comm. Statist. Simul.Comput. 32 (2): 419-435.Search in Google Scholar

Kumar, M., Mishra, N. and Gupta, R. (2008).Predictive Performance of the Improved Estimators with Exact Restrictions in Linear Regression Models.Amer. J. Math. Management Sci. 28: 419-432.Search in Google Scholar

McDonald, G.C., Galarneau, D.I. (1975). A Monte Carlo Evaluation of Some Ridge Type Estimators.J. Amer. Statist. Assoc. 20: 407-416.Search in Google Scholar

Özbay, N., Kaçıranlar, S. and Dawoud I. (2016).The Feasible Generalized Restricted Ridge Regression Estimator. J. Stat. Comput. Simul. DOI: 10.1080/00949655.2016.1224880.10.1080/00949655.2016.1224880Search in Google Scholar

Shalabh, S. (1995).Performance of Stein-Rule Procedure for Simultaneous Prediction of Actual and Average Values of Study Variable in Linear Regression Model.Bull. Int. Stat. Ins. 56: 1375-1390.Search in Google Scholar

Shalabh, S., Toutenburg, H. and Heumann, C. (2009).Stein-Rule Estimation Under an Extended Balanced Loss Function. J. Stat. Comput. Simul. 79 (10): 1259-1273.Search in Google Scholar

Srivastava, V.K., Srivastava, A.K. (1983). Improved Estimation of Coefficients in Regression Models With Incomplete Prior Information.Biom. J. 25: 775-782.Search in Google Scholar

Srivastava, V.K., Srivastava, A.K. (1984). Stein-Rule Estimators in Restricted Regression Models.Esdadistica. 36: 89-98.Search in Google Scholar

Srivastava, A.K., Chandra, R. (1991). Improved Estimation of Restricted Regression Model When Disturbances are Not Necessarily Normal. Sankhya, Ser. B. 53: 119-133.Search in Google Scholar

Stein, C. (1956). Inadmissibility of Usual Estimator for the Mean of a Multivariate Normal Distribution.Proc. Third Berkeley Symp.on Math. Statist.and Prob., Vol. 1, Univ. of Calif. Press, 197- 206, Berkeley.10.1525/9780520313880-018Search in Google Scholar

Toutenburg, H., Shalabh, S. (1996). Predictive Performance of the Methods of Restricted and Mixed Regression Estimators.Biom. J. 38 (8): 951-959.Search in Google Scholar

Toutenburg, H., Shalabh, S. (2000). Improved Predictions in Linear Regression Models with Stochastic Linear Constraints.Biom. J. 42: 71-86.Search in Google Scholar

Trenkler, G. (1984). On the Performance of Biased Estimators in the Linear Regression Model with Correlated or Heteroscedastic Errors. J. Econometrics. 25: 179-190.Search in Google Scholar

Wan, A.T.K., Chaturvedi, A. (2000). Operational Variants of the Minimum Mean Squared Error Estimator in Linear Regression Models with Non-Spherical Disturbances. Ann. Inst. Statist.Math. 52: 332-342.Search in Google Scholar