Robust estimation in parametric time series models under long- and short-range-dependent structures

Jiti Gao*, Degui Li, Zhengyan Lin

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

This paper studies the asymptotic behaviour of an M-estimator of regression parameters in the linear model when the design variables are either stationary short-range dependent (SRD), alpha-mixing or long-range dependent (LRD), and the errors are LRD. The weak consistency and the asymptotic distributions of the M-estimator are established. We present some simulated examples to illustrate the efficiency of the proposed M-estimation method.

Original languageEnglish
Pages (from-to)161-181
Number of pages21
JournalAustralian & new zealand journal of statistics
Volume51
Issue number2
DOIs
Publication statusPublished - Jun 2009

Keywords

  • LINEAR-MODELS
  • long-range dependence
  • linear regression models
  • consistency
  • BEHAVIOR
  • REGRESSION-MODELS
  • ASYMPTOTIC NORMALITY
  • alpha-mixing
  • SEMIPARAMETRIC REGRESSION
  • M-estimation
  • asymptotic normality
  • MEMORY ERRORS

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