Preliminary test almost unbiased two-parameter estimators with student’s t errors and conflicting test statistics

Xinfeng Chang and Hexiang Wang

Communications in Statistics - Theory and Methods, 2019, vol. 48, issue 18, 4449-4473

Abstract: In this paper, we consider the preliminary test approach to the estimation of the regression parameter in a multiple regression model under multicollinearity situation. The preliminary test almost unbiased two-parameter estimators based on the Wald, the Likelihood ratio, and the Lagrangian multiplier tests are given, when it is suspected that the regression parameter may be restricted to a subspace and the regression error is distributed with multivariate Student’s t errors. The bias and quadratic risk of the proposed estimators are derived and compared. Furthermore, a Monte Carlo simulation is provided to illustrate some of the theoretical results.

Date: 2019
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DOI: 10.1080/03610926.2018.1502782

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