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On the asymptotic normality of the R-estimators of the slope parameters of simple linear regression models with associated errors |
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| Authors: | Sana Louhichi Ryozo Miura Dalibor Volný |
| Institution: | 1. Laboratoire Jean Kuntzmann, Saint Martin d'Hères, Francesana.louhichi@imag.fr;3. National Center of Sciences, Graduate School of International Corporate Strategy, Hitotsubashi University, Tokyo, Japan;4. Graduate School of Economics and Management, Tohoku University, Sendai, Japan;5. Département de Mathématiques, Université de Rouen, Saint Etienne du Rouvray, France |
| Abstract: | ABSTRACTThe purpose of this paper is to prove, under mild conditions, the asymptotic normality of the rank estimator of the slope parameter of a simple linear regression model with stationary associated errors. This result follows from a uniform linearity property for linear rank statistics that we establish under general conditions on the dependence of the errors. We prove also a tightness criterion for weighted empirical process constructed from associated triangular arrays. This criterion is needed for the proofs which are based on that of Koul Behavior of robust estimators in the regression model with dependent errors. Ann Stat. 1977;5(4):681–699] and of Louhichi Louhichi S. Weak convergence for empirical processes of associated sequences. Ann Inst Henri Poincaré Probabilités Statist. 2000;36(5):547–567]. |
| Keywords: | Robust estimators r-estimators linear models rank statistics dependent errors association mixing asymptotic normality weighted empirical processes |