A. Jahufer, “Detecting Global Influential Observations in Liu Regression Model,” Open Journal of Statistics, Vol. 3, No. 1, 2013, pp. 5-11. http://dx.doi.org/10.4236/ojs.2013.31002
has been cited by the following article:
TITLE: Identifying Unusual Observations in Ridge Regression Linear Model Using Box-Cox Power Transformation Technique
AUTHORS: Aboobacker Jahufer
KEYWORDS: Box-Cox Transformation; Ridge Regression; Constant Variance Perturbation; Local Influence; Influential Observations
JOURNAL NAME: Open Journal of Statistics, Vol.4 No.1, January 27, 2014
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.