A weighted estimator of conditional hazard rate with left-truncated and dependent data

Based on empirical likelihood method, we construct new weighted estimators of conditional density and conditional survival functions when the interest random variable is subject to random left-truncation; further, we define a plug-in weighted estimator of the conditional hazard rate. Under strong mi...

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Bibliographic Details
Published in:Annals of the Institute of Statistical Mathematics 2018-02, Vol.70 (1), p.155-189
Main Authors: Liang, Han-Ying, Ould Saïd, Elias
Format: Article
Language:English
Subjects:
Confidence intervals
Economic models
Economics
Estimating techniques
Estimators
Finance
Insurance
Management
Mathematics
Mathematics and Statistics
Normality
Random variables
Statistics
Statistics for Business
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Summary:Based on empirical likelihood method, we construct new weighted estimators of conditional density and conditional survival functions when the interest random variable is subject to random left-truncation; further, we define a plug-in weighted estimator of the conditional hazard rate. Under strong mixing assumptions, we derive asymptotic normality of the proposed estimators which permit to built a confidence interval for the conditional hazard rate. The finite sample behavior of the estimators is investigated via simulations too.
ISSN:0020-3157
1572-9052
DOI:10.1007/s10463-016-0587-4