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Local linear kernel estimation of the discontinuous regression function

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Abstract

We address the problems of estimating the discontinuous regression function and also its jump points. We propose a method in two steps: we first estimate the jumps and finally the regression function is estimated by an adapted version of a local linear smoother which makes use of the estimated jumps. The practical performance of the proposed method is evaluated by using simulation studies and an application to a real-life problem.

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Acknowledgments

The authors would like to thank the associate editor and referees for their many helpful comments and suggestions. This research was partially supported by MCYT (Spain) contract n. BFM2001-3190.

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Authors and Affiliations

  1. Departamento de Estadística e Investigación Operativa, Facultad de Ciencias, Universidad de Granada, Campus de Fuentenueva, s/n, 18071, Granada, Spain

    I. R. Sánchez-Borrego, M. D. Martínez-Miranda & A. González-Carmona

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  1. I. R. Sánchez-Borrego
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  2. M. D. Martínez-Miranda
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  3. A. González-Carmona
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Correspondence to I. R. Sánchez-Borrego.

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Sánchez-Borrego, I.R., Martínez-Miranda, M.D. & González-Carmona, A. Local linear kernel estimation of the discontinuous regression function. Computational Statistics 21, 557–569 (2006). https://doi.org/10.1007/s00180-006-0014-z

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