r ?k Class estimator in the linear regression model with correlated errors

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• 作者：Gülesen üstündagˇ ?iray (1)
  Selahattin Ka??ranlar (1)
  Sadullah Sakall?o?lu (1)
  
• 关键词：Autocorrelation ; Multicollinearity ; r ?k Class estimator ; Ridge regression estimator ; Mean square error matrix
• 刊名：Statistical Papers
• 出版年：2014
• 出版时间：May 2014
• 年：2014
• 卷：55
• 期：2
• 页码：393-407
• 全文大小：223 KB
• 参考文献：1. Aitken AC (1935) On least squares and linear combinations of observations. Proc R Soc Edinb 55: 42-8
  2. Baye MR, Parker DF (1984) Combining ridge and principal component regression: a money demand illustration. Commun Stat Theory Methods 13: 197-05 CrossRef
  3. Bayhan GM, Bayhan M (1998) Forecasting using autocorrelated errors and multicollinear predictor variables. Comp Ind Eng 34(2): 413-21 CrossRef
  4. Farebrother RW (1976) Further results on the mean square error of ridge regression. J R Stat Soc Ser B Methodol 38(3): 248-50
  5. Firinguetti L (1989) A simulation study of ridge regression estimators with autocorrelated errors. Commun Stat Simul 18(2): 673-02 CrossRef
  6. Graybill FA (1976) Theory and application of the linear model. Duxbury Press, Pacific Grove
  7. Griffiths WE, Hill RC, Judge GC (1993) Learning and practicing econometrics. Wiley, New York
  8. Güler H, Ka??ranlar S (2009) A comparison of mixed and ridge estimators of linear models. Commun Stat Simul Comput 38: 2, 368-01 CrossRef
  9. Hoerl AE, Kennard RW (1970) Ridge regression: biased estimation for non-orthogonal problems. Technometrics 12: 55-7 CrossRef
  10. Kibria BMG (2003) Performance of some new ridge regression estimators. Commun Stat Simul Comput 32(2): 419-35 CrossRef
  11. McDonald GC, Galarneau DI (1975) A monte carlo evaluation of some ridge-type estimators. J Am Stat Assoc 20: 407-16 CrossRef
  12. Nomura M, Ohkubo T (1985) A note on combining ridge and principal component regression. Commun Stat Theory Methods 14: 2489-493 CrossRef
  13. Obenchain RL (1975) Ridge analysis following a preliminary test of the shrunken hypothesis. Technometrics 17: 431-45 CrossRef
  14. Sarkar N (1996) Mean square error matrix comparison of some estimators in linear regressions with multicollinearity. Stat Probab Lett 30: 133-38 CrossRef
  15. Trenkler G (1984) On the performance of biased estimators in the linear regression model with correlated or heteroscedastic errors. J Econom 25: 179-90 CrossRef
  16. Trenkler G, Trenkler D (1983) A note on superiority comparisons of homogeneous linear estimators. Commun Stat A Theory Methods 12(7): 799-08 CrossRef
  17. Trenkler G, Toutenburg H (1990) Mean squared error matrix comparisons between biased estimators: an overview of recent results. Stat Papers 31(3): 165-79 CrossRef
  
• 作者单位：Gülesen üstündagˇ ?iray (1)
  Selahattin Ka??ranlar (1)
  Sadullah Sakall?o?lu (1)
  
  1. Department of Statistics, Faculty of Science and Letters, Cukurova University, Adana, 01330, Turkey
  
• ISSN：1613-9798

文摘

Autocorrelation in errors and multicollinearity among the regressors are serious problems in regression analysis. The aim of this paper is to examine multicollinearity and autocorrelation problems concurrently and to compare the r ?k class estimator to the generalized least squares estimator, the principal components regression estimator and the ridge regression estimator by the scalar and matrix mean square error criteria in the linear regression model with correlated errors.