Efficient empirical likelihood inference for recovery rate of COVID19 under double-censoring
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Publication:2156816
DOI10.1016/j.jspi.2022.04.005OpenAlexW3082384733MaRDI QIDQ2156816
Yanchun Bao, Jie Hu, Hongsheng Dai, Wei Liang
Publication date: 20 July 2022
Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.jspi.2022.04.005
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Cites Work
- Analysis of Doubly-Censored Survival Data, with Application to AIDS
- Weak convergence of a self-consistent estimator of the survival function with doubly censored data
- A large sample study of generalized maximum likelihood estimators from incomplete data via self-consistency
- Strong consistency of a nonparametric estimator of the survival function with doubly censored data
- Empirical likelihood and general estimating equations
- Linear regression with doubly censored data
- Semiparametric likelihood ratio inference
- Regression \(M\)-estimators with doubly censored data
- Empirical likelihood confidence regions for one- or two-samples with doubly censored data
- Efficient real-time monitoring of an emerging influenza pandemic: how feasible?
- Semiparametric theory and missing data.
- Quantile Regression for Doubly Censored Data
- Empirical likelihood ratio confidence intervals for a single functional
- Nonparametric Estimation of a Survivorship Function with Doubly Censored Data
- Non-Parametric Survival Analysis of Infectious Disease Data
- Weighted empirical likelihood ratio confidence intervals for the mean with censored data
- Empirical likelihood for a class of functionals of survival distribution with censored data
