Nonlinear wavelet estimator of the regression function under left-truncated dependent data

Jacobo de Uña-Álvarez, Han-Ying Liang and Alberto Rodríguez-Casal

Journal of Nonparametric Statistics, 2010, vol. 22, issue 3, 319-344

Abstract: In this paper, we define a new nonlinear wavelet-based estimator of the regression function under random left-truncation. We provide an asymptotic expression for the mean integrated squared error (MISE) of the estimator. It is assumed that the observations form a stationary α-mixing sequence. The nonlinear wavelet-based estimator of the covariate's density is considered as well. Unlike for kernel estimators, the MISE expression of the wavelet-based estimators is not affected by the presence of discontinuities in the curves. The finite sample behaviour of the proposed estimators is explored through simulations.

Date: 2010
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Citations: View citations in EconPapers (3)

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DOI: 10.1080/10485250903469736

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