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

• 作者: Aboobacker Jahufer
• 来源期刊: 统计学期刊(英文)
• 学科: 数学
• 关键词: Box-Cox Transformation RIDGE Regression CONSTANT Variance PERTURBATION Local Influence Influential OBSERVATIONS
• 年，卷（期）: 2014,（1）
• 页码范围: 19-26
• 页数: 8页
• 分类号: O1

摘要

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.