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.