The abstract of doctoral dissertation ‘nonlinear wavelet density estimation and hazard rate estimation with data missing at random’

Yuye Zou, Guoliang Fan and Riquan Zhang

Statistical Theory and Related Fields, 2020, vol. 4, issue 1, 117-119

Abstract: In this thesis, we establish non-linear wavelet density estimators and studying the asymptotic properties of the estimators with data missing at random when covariates are present. The outstanding advantage of non-linear wavelet method is estimating the unsoothed functions, however, the classical kernel estimation cannot do this work. At the same time, we study the larger sample properties of the ISE for hazard rate estimator.

Date: 2020
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DOI: 10.1080/24754269.2019.1653161

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