A vine copula approach for regression analysis of bivariate current status data with informative censoring-Reference-Cited by-同舟云学术

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A vine copula approach for regression analysis of bivariate current status data with informative censoring

Published:2020-01-02 Issue:1 Volume:32 Page:185-200
ISSN:1048-5252
Container-title:Journal of Nonparametric Statistics
language:en
Short-container-title:Journal of Nonparametric Statistics

Author:

Li Huiqiong¹,Ma Chenchen²,Li Ni³,Sun Jianguo²

Affiliation:

1. Department of Statistics, Yunnan University, Yunnan, People's Republic of China

2. Department of Statistics, University of Missouri, Columbia, MO, USA

3. School of Mathematics and Statistics, Hainan Normal University, Huainan, People's Republic of China

Publisher

Informa UK Limited

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Link

https://www.tandfonline.com/doi/pdf/10.1080/10485252.2019.1710506

Reference35 articles.

1. Pair-copula constructions of multiple dependence

2. Vine copula based likelihood estimation of dependence patterns in multivariate event time data

3. Efficient Estimation of Semiparametric Multivariate Copula Models

4. Semiparametric transformation models for current status data with informative censoring

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Estimation of the additive hazards model based on case‐cohort interval‐censored data with dependent censoring;Canadian Journal of Statistics;2024-07-12

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