Asymptotic Normality of the Nonparametric Kernel Estimation of the Conditional Hazard Function for Left-Truncated and Dependent Data
Year: 2018
Author: Meijuan Ou, Xianzhu Xiong, Yi Wang
Annals of Applied Mathematics, Vol. 34 (2018), Iss. 4 : pp. 395–406
Abstract
Under some mild conditions, we derive the asymptotic normality of the Nadaraya-Watson and local linear estimators of the conditional hazard function for left-truncated and dependent data. The estimators were proposed by Liang and Ould-Saïd [1]. The results confirm the guess in Liang and Ould-Saïd [1].
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Journal Article Details
Publisher Name: Global Science Press
Language: English
DOI: https://doi.org/2018-AAM-20587
Annals of Applied Mathematics, Vol. 34 (2018), Iss. 4 : pp. 395–406
Published online: 2018-01
AMS Subject Headings: Global Science Press
Copyright: COPYRIGHT: © Global Science Press
Pages: 12
Keywords: asymptotic normality Nadaraya-Watson estimation local linear estimation conditional hazard function left-truncated data.