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Robust regression smoothing for dependent observations

Tae Yoon Kim|Gyu Moon Song|Jang Han Kim
대한수학회 (The Korean Mathematical Society)|2004.04|대한수학회논문집 (Communications of the KMS)|제19권 제2호|pp. 345-354

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Abstract

Boente and Fraiman cite{1989b} studied robust nonparametricestimators for regression or autoregression problems when theobservations exhibit serial dependence. They established strongconsistency of two families of M-type robust equivariantestimators for phi-mixing processes. In this paper we extendtheir results to weaker alpha-mixing processes.

참고문헌 (7)

  1. "{\it Robust nonparametric regression estimation}", 29, pp.180~198 (1989)
  2. "\it Robust nonparametricregression estimation for dependent observations}", pp.1242~ (1989)
  3. "\it Strong uniform convergence rates in robust nonparametrictime series and prediction", pp.77~ (1984)
  4. "{\it Moment bounds for mixingrandom variables useful in nonparametric function estimation}", 56, pp.151~159 (1995)
  5. "\it On estimating regression}", pp.141~ (1964)
  6. "\it Nonparametric estimators for time series}"
  7. "Robust and Nonlinear Time Series Analysis. Lecture Notes in Statist.", \it robust(nparametric autoregression}), pp.247~ (1984)

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