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Noise benefits to robust M-estimation of location in dependent observations

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  • Pan, Yan
  • Ren, Yuhao
  • Duan, Fabing

Abstract

In the presence of weakly dependent noise, we analyze the asymptotic efficiency of robust maximum likelihood type estimators (M-estimators) for location estimation. We observe the noise-enhanced asymptotic efficiency effect by tuning the background noise level for a single M-estimator. We also theoretically derive the asymptotic efficiency of a parallel array of M-estimators, and illustrate the possibility of the noise enhancement of the asymptotic efficiency by injecting extra additive noise components. These obtained results enrich the research of noise benefits for the robust estimation of location from the dependent observations.

Suggested Citation

  • Pan, Yan & Ren, Yuhao & Duan, Fabing, 2018. "Noise benefits to robust M-estimation of location in dependent observations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 144-152.
    • Handle: RePEc:eee:phsmap:v:505:y:2018:i:c:p:144-152
    DOI: 10.1016/j.physa.2018.03.027
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    References listed on IDEAS

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