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Local polynomial estimation of a conditional mean function with dependent truncated data

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Abstract

By applying local polynomial regression, we propose an estimator of a conditional mean function and its derivatives under a left truncation model. The target function includes the regression function, the conditional moment as well as the conditional distribution function as special cases. It is assumed that the observations form a stationary α-mixing sequence. Asymptotic normality of the estimator is established. The finite sample behavior of the estimator is investigated via simulations, too.

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Authors and Affiliations

  1. Department of Mathematics, Tongji University, Shanghai, 200092, P.R. China

    Han-Ying Liang

  2. Department of Statistics and OR, Facultad de Ciencias Económicas y Empresariales, Universidad de Vigo, Campus Lagoas-Marcosende, 36310, Vigo, Spain

    Han-Ying Liang & Jacobo de Uña-Álvarez

  3. Department of Statistics and OR, Escuela de Ingeniería Forestal, Universidad de Vigo, Campus A Xunqueira, 36005, Pontevedra, Spain

    María del Carmen Iglesias-Pérez

Authors
  1. Han-Ying Liang
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  2. Jacobo de Uña-Álvarez
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  3. María del Carmen Iglesias-Pérez
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Correspondence to Han-Ying Liang.

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Liang, HY., de Uña-Álvarez, J. & Iglesias-Pérez, M.d.C. Local polynomial estimation of a conditional mean function with dependent truncated data. TEST 20, 653–677 (2011). https://doi.org/10.1007/s11749-011-0234-6

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  • DOI: https://doi.org/10.1007/s11749-011-0234-6

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