Influential diagnostics with Pena’s statistic for the modified ridge regression

References

• Amanullah, M., G. R. Pasha, and M. Aslam. 2013. Local influence diagnostics in the modified ridge regression. Communications in Statistics – Theory and Methods 42:1851–69. doi:https://doi.org/10.1080/03610926.2011.597920.
   Web of Science ®Google Scholar
• Amanullah, M., G. R. Pasha, and M. Aslam. 2014. Influence in the elliptical modified ridge regression. Communications in Statistics – Theory and Methods 43 (21):4650–67. doi:https://doi.org/10.1080/03610926.2012.737497.
   Web of Science ®Google Scholar
• Adewale, F., J. Lukman, Oyedeji, and R. Abiola. 2016. Modified Pena’s measure for detecting influential observations in biased estimators. Zimbabwe Journal of Science and Technology 2:58–65.
   Google Scholar
• Akdeniz, F., and M. Roozbeh. 2017. Efficiency of the generalized difference-based weighted mixed almost unbiased two parameter estimator in Partially Linear Model. Communications in Statistics – Theory and Methods 46 (24):12259–80. doi:https://doi.org/10.1080/03610926.2017.1295075.
   Web of Science ®Google Scholar
• Atkinson, A. C. 1985. Plots, transformations and regression. Oxford, UK: Clarendon Press.
   Google Scholar
• Belsley, D. A., E. Kuh, and R. E. Welsch. 1980. Regression diagnostics: Identifying influential data and sources of collinearity. New York: John Wiley & Sons.
   Google Scholar
• Chatterjee, S., and A. S. Hadi. 1988. Sensitivity analysis in linear regression. New York: John Wiley & Sons.
   Google Scholar
• Cook, R. D. 1977. Detection of influential observation in linear regression. Technometrics 19:15–8. doi:https://doi.org/10.2307/1268249.
   Web of Science ®Google Scholar
• Cook, R. D., and S. Weisberg. 1982. Residuals and influence in regression. New York: Chapman & Hall.
   Google Scholar
• Emami, H., and M. Emami. 2016. New influence diagnostics in ridge regression. Journal of Applied Statistics 43 (3):476–89.
   Web of Science ®Google Scholar
• Hoerl, A. E., and R. W. Kennard. 1970. Ridge regression: Biased estimation for non-orthogonal problems. Technometrics 12 (1):55–67.
   Web of Science ®Google Scholar
• Jahufer, A., and C. Jianbao. 2009. Assessing global influential observations in modified ridge regression. Statistics and Probability Letters 79 (4):513–8.
   Web of Science ®Google Scholar
• Kashif, M., M. Amanullah, and M. Aslam. 2018. Pena’s statistic for the Liu regression. Journal of Statistical Computation and Simulation 88 (13):2473–88.
   Web of Science ®Google Scholar
• Longley, J. W. 1967. An appraisal of least squares programs for the electronic computer from the point of view of the user. Journal of the American Statistical Association 62 (319):819–41.
   Web of Science ®Google Scholar
• Li, Y., and H. Yang. 2011. On the performance of the jackknifed modified ridge estimator in the linear regression models with correlated or heteroscedastic errors. Communications in Statistics – Theory and Methods 40 (15):2695–708.
   Web of Science ®Google Scholar
• McDonald, G. C., and D. I. Galarneau. 1975. A Monte Carlo evaluation of some ridge – type estimators. Journal of the American Statistical Association 70 (350):407–16.
   Web of Science ®Google Scholar
• Newhouse, J. P., Oman. S. D. 1971. An evaluation of ridge estimators. Rand Report, No. R-716-PR, 1–28.
   Google Scholar
• Pena, D. 2005. A new statistic for influence in linear regression. Technometrics 47:1–12.
   Web of Science ®Google Scholar
• Roozbeh, M. 2016. Robust ridge estimator in restricted semiparametric regression models. Journal of Multivariate Analysis 147:127–44.
   Web of Science ®Google Scholar
• Shi, L., and X. Wang. 1999. Local influence in ridge regression. Computational Statistics & Data Analysis 31:341–53.
   Web of Science ®Google Scholar
• Swindel, B. F. 1976. Good ridge estimators based on prior information. Communications in Statistics – Theory and Methods 17:1065–75.
   Web of Science ®Google Scholar
• Ullah, M. A., and G. R. Pasha. 2009. The origin and developments of influence measures in regression. Pakistan Journal of Statistics 25:295–307.
   Web of Science ®Google Scholar
• Walker, E., and J. B. Birch. 1988. Influence measures in ridge regression. Technometrics 30 (2):221–7. doi:https://doi.org/10.2307/1270168.
   Web of Science ®Google Scholar
• Wijekoon, P. 1998. A comparison of the restricted ridge regression and the modified ridge regression estimators. Ceylon Journal of Science: Physical Sciences 5:75–9.
   Google Scholar