r-d Class Estimator Under Misspecification

Gülesen Üstündaĝ Şiray

Communications in Statistics - Theory and Methods, 2015, vol. 44, issue 22, 4742-4756

Abstract: Omission of some relevant explanatory variables and multicollinearity in regression models are very serious problems in applied works. There are some papers examining the multicollinearity and misspecification which is due to omission of some relevant explanatory variables, concurrently. To remedy the problem of multicollinearity, Kaçıranlar and Sakallıoğlu (2001) proposed the r-d class estimator that includes the ordinary least squares, principal components regression, and Liu estimators as special cases. The aim of this paper is to examine the performance of the r-d class estimator in misspecificied linear models.

Date: 2015
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DOI: 10.1080/03610926.2013.835421

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