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M-estimation in nonparametric regression under strong dependence and infinite variance

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  • Ngai Chan

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  • Rongmao Zhang

    ()

Abstract

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Suggested Citation

  • Ngai Chan & Rongmao Zhang, 2009. "M-estimation in nonparametric regression under strong dependence and infinite variance," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 61(2), pages 391-411, June.
  • Handle: RePEc:spr:aistmt:v:61:y:2009:i:2:p:391-411 DOI: 10.1007/s10463-007-0142-4
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    References listed on IDEAS

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    1. Liang Peng & Qiwei Yao, 2004. "Nonparametric regression under dependent errors with infinite variance," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, pages 73-86.
    2. Hall, Peter & Hart, Jeffrey D., 1990. "Nonparametric regression with long-range dependence," Stochastic Processes and their Applications, Elsevier, vol. 36(2), pages 339-351, December.
    3. Knight, Keith, 1993. "Estimation in Dynamic Linear Regression Models with Infinite Variance Errors," Econometric Theory, Cambridge University Press, vol. 9(04), pages 570-588, August.
    4. Koul, Hira L. & Surgailis, Donatas, 2001. "Asymptotics of empirical processes of long memory moving averages with infinite variance," Stochastic Processes and their Applications, Elsevier, vol. 91(2), pages 309-336, February.
    5. Pollard, David, 1991. "Asymptotics for Least Absolute Deviation Regression Estimators," Econometric Theory, Cambridge University Press, vol. 7(02), pages 186-199, June.
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    Cited by:

    1. Toshio Honda, 2013. "Nonparametric quantile regression with heavy-tailed and strongly dependent errors," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, pages 23-47.

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