Asymptotic behavior for S-estimators in random design linear model with long-range-dependent errors

Research output: Contribution to journalArticlepeer-review



Publication details

DatePublished - Nov 2007
Issue number3
Number of pages15
Pages (from-to)289-303
Original languageEnglish


The asymptotic behavior of S-estimators in a random design linear model with long-range-dependent Gaussian errors is considered. It turns out that the S-estimators of regression parameter and error variance are strongly consistent under mild conditions. Furthermore, the asymptotic distribution of the S-estimator of regression parameter is normal if the design vectors are i.i.d. and is non-normal if the design vectors are long-range dependent Gaussian vectors. We also show that the asymptotic distribution of S-estimator of the error variance is non-normal since the errors are long-range dependent.

    Research areas

  • long-range dependence, CONVERGENCE, S-estimator, consistency, linear model, asymptotic distribution, REGRESSION MODEL

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