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ASYMPTOTIC NORMALITY OF THE DECONVOLUTION KERNEL DENSITY ESTIMATORS BASED ON INDEPENDENT AS WELL AS STRONG MIXING RIGHT CENSORED DATA
(2020-08-10)
We consider estimation of a density when observed lifetime from the convolution model contaminated by additive measurement errors. A kernel type deconvolution density estimator of the unknown distribution based on right ...
A Necessary and Sufficient Condition for the Asymptotic Normality of the Quantile Estimator in the Deconvolution Problem
(2022-05-16)
**Please note that the full text is embargoed until 5/10/2024** ABSTRACT: In this study, we examine the estimation of a quantile function when we have n observations coming from the convolution model contaminated by additive ...
Asymptotic Properties of the Deconvolution Kernel Density Estimate based on 2-Dependent Error Structure with Applications to Remaining Useful Life Problems in Reliability Theory
This thesis is motivated from an engineering question, which led us to the deconvolution problem with a dependent error structure. We establish a deconvolution kernel density estimator by adapting the methods of kernel ...