Kernel estimation of conditional density with truncated, censored and dependent data

Han-Ying Liang and Ai-Ai Liu

Journal of Multivariate Analysis, 2013, vol. 120, issue C, 40-58

Abstract: In this paper we define a kernel estimator of the conditional density for a left-truncated and right-censored model based on the generalized product-limit estimator of the conditional distributed function. Under the observations with multivariate covariates form a stationary α-mixing sequence, we derive the asymptotic normality as well as a Berry–Esseen type bound for the proposed estimator. Also, the uniform convergence with rates for the estimator is considered. Finite sample behavior of the estimator is investigated via simulations too.

Keywords: Asymptotic normality; Berry–Esseen type bound; Uniform convergence; Truncated and censored; Conditional density; α-mixing (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (4)

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DOI: 10.1016/j.jmva.2013.05.009

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