Identifying Unusual Observations in Ridge Regression Linear Model Using Box-Cox Power Transformation Technique

Aboobacker Jahufer

doi:10.4236/ojs.2014.41003

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Open Journal of Statistics > Vol.4 No.1, February 2014

Identifying Unusual Observations in Ridge Regression Linear Model Using Box-Cox Power Transformation Technique ()

Department of Mathematical Sciences, Faculty of Applied Sciences, South Eastern University of Sri Lanka, Sammanthurai, Sri Lanka.

DOI: 10.4236/ojs.2014.41003 PDF HTML 9,249 Downloads 16,266 Views Citations

Abstract

The use of [1] Box-Cox power transformation in regression analysis is now common; in the last two decades there has been emphasis on diagnostics methods for Box-Cox power transformation, much of which has involved deletion of influential data cases. The pioneer work of [2] studied local influence on constant variance perturbation in the Box-Cox unbiased regression linear mode. Tsai and Wu [3] analyzed local influence method of [2] to assess the effect of the case-weights perturbation on the transformation-power estimator in the Box-Cox unbiased regression linear model. Many authors noted that the influential observations on the biased estimators are different from the unbiased estimators. In this paper I describe a diagnostic method for assessing the local influence on the constant variance perturbation on the transformation in the Box-Cox biased ridge regression linear model. Two real macroeconomic data sets are used to illustrate the methodologies.

Keywords

Box-Cox Transformation; Ridge Regression; Constant Variance Perturbation; Local Influence; Influential Observations

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A. Jahufer, "Identifying Unusual Observations in Ridge Regression Linear Model Using Box-Cox Power Transformation Technique," Open Journal of Statistics, Vol. 4 No. 1, 2014, pp. 19-26. doi: 10.4236/ojs.2014.41003.

Conflicts of Interest

The authors declare no conflicts of interest.

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