Three Contributions to Robust Regression Diagnostics

0456162 - ÚI 2016 RIV SK eng J - Journal Article
Kalina, Jan
Three Contributions to Robust Regression Diagnostics.
Journal of applied mathematics, statistics and informatics. Roč. 11, č. 2 (2015), s. 69-78. ISSN 1336-9180
Grant - others:GA ČR(CZ) GA13-01930S; Nadační fond na podporu vědy(CZ) Neuron
Institutional support: RVO:67985807
Keywords : robust regression * robust econometrics * hypothesis testing
Subject RIV: BA - General Mathematics
http://www.degruyter.com/view/j/jamsi.2015.11.issue-2/jamsi-2015-0013/jamsi-2015-0013.xml?format=INT

Robust regression methods have been developed not only as a diagnostic tool for standard least squares estimation in statistical and econometric applications, but can be also used as self-standing regression estimation procedures. Therefore, they need to be equipped by their own diagnostic tools. This paper is devoted to robust regression and presents three contributions to its diagnostic tools or estimating regression parameters under non-standard conditions. Firstly, we derive the Durbin-Watson test of independence of random regression errors for the regression median. The approach is based on the approximation to the exact null distribution of the test statistic. Secondly, we accompany the least trimmed squares estimator by a subjective criterion for selecting a suitable value of the trimming constant. Thirdly, we propose a robust version of the instrumental variables estimator. The new methods are illustrated on examples with real data and their advantages and limitations are discussed.
Permanent Link: http://hdl.handle.net/11104/0256733