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Asymptotic uniform linearity of some robust statistics under exponentially subordinated strongly dependent models

Research output: Contribution to journalJournal article

<mark>Journal publication date</mark>15/08/1999
<mark>Journal</mark>Statistics and Probability Letters
Issue number2
Number of pages10
Pages (from-to)137-146
<mark>Original language</mark>English


In this paper, we discuss an asymptotic distributional theory of three broad classes of robust estimators of the regression parameter namely, L-, M- and R-estimators in a linear regression model when the errors are generated by an exponentially
subordinated strongly dependent process. The results are obtained as a consequence of an asymptotic uniform Taylor-type expansion of certain randomly weighted empirical processes. The limiting distributions of the estimators are nonnormal and depend on the rst nonzero index of the Laguerre polynomial expansion of a class of indicator functions of the error random variables.