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ESTIMATING ADDITIVE NONPARAMETRIC MODELS BY PARTIAL Lq NORM: THE CURSE OF FRACTIONALITY

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  • Linton, Oliver

Abstract

We propose a new method for estimating additive nonparametric regression models based on taking the Lq median of a sample of kernel estimators. We establish the consistency and asymptotic normality of our procedures. The rate of convergence depends on the value of q. For q > 3/2 one has the usual one-dimensional rate, but if q [less-than-or-equal] 3/2 the rate can be slower.

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Bibliographic Info

Article provided by Cambridge University Press in its journal Econometric Theory.

Volume (Year): 17 (2001)
Issue (Month): 06 (December)
Pages: 1037-1050

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Handle: RePEc:cup:etheor:v:17:y:2001:i:06:p:1037-1050_17

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Cited by:
  1. Gao, Jiti, 2007. "Nonlinear time series: semiparametric and nonparametric methods," MPRA Paper 39563, University Library of Munich, Germany, revised 01 Sep 2007.
  2. Efang Kong & Oliver Linton & Yingcun Xia, 2009. "Uniform Bahadur Representation for LocalPolynomial Estimates of M-Regressionand Its Application to The Additive Model," STICERD - Econometrics Paper Series, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE /2009/535, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
  3. Efang Kong & Oliver Linton & Yingcun Xia, 2011. "Global Bahadur representation for nonparametric censored regression quantiles and its applications," CeMMAP working papers, Centre for Microdata Methods and Practice, Institute for Fiscal Studies CWP33/11, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

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