Nonlinear wavelet density estimation with data missing at random when covariates are present

Yu-Ye Zou, Han-Ying Liang () and Jing-Jing Zhang

Metrika: International Journal for Theoretical and Applied Statistics, 2015, vol. 78, issue 8, 967-995

Abstract: In this paper, we construct the nonlinear wavelet estimator of a density with data missing at random when covariables are present, and provide an asymptotic expression for the mean integrated squared error (MISE) of the estimator. Unlike for kernel estimators, the MISE expression of the wavelet-based estimator still holds when the density function is piecewise smooth. Also, the asymptotic normality of the estimator is established. Copyright Springer-Verlag Berlin Heidelberg 2015

Keywords: Nonlinear wavelet density estimator; Mean integrated squared error; Missing data; Asymptotic normality; 62G07; 62G20 (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:spr:metrik:v:78:y:2015:i:8:p:967-995

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DOI: 10.1007/s00184-015-0536-x

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