Asymptotic normality of conditional density estimation under truncated, censored and dependent data

Han-Ying Liang, Hong-Bing Zhou and Qiu-Li Guo

Communications in Statistics - Theory and Methods, 2020, vol. 49, issue 22, 5371-5391

Abstract: In this paper, we focus on the left-truncated and right-censored model, and construct the local linear and Nadaraya-Watson type estimators of the conditional density. Under suitable conditions, we establish the asymptotic normality of the proposed estimators when the observations are assumed to be a stationary α-mixing sequence. Finite sample behavior of the estimators is investigated via simulations too.

Date: 2020
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DOI: 10.1080/03610926.2019.1619769

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