A vine copula approach for regression analysis of bivariate current status data with informative censoring
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Publication:5221304
DOI10.1080/10485252.2019.1710506zbMath1437.62182OpenAlexW2999088739WikidataQ126397767 ScholiaQ126397767MaRDI QIDQ5221304
Chenchen Ma, Ni Li, Jianguo Sun, Hui-Qiong Li
Publication date: 25 March 2020
Published in: Journal of Nonparametric Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/10485252.2019.1710506
Nonparametric regression and quantile regression (62G08) Censored data models (62N01) Characterization and structure theory for multivariate probability distributions; copulas (62H05)
Uses Software
Cites Work
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- Pair-copula constructions of multiple dependence
- Goodness-of-fit tests for copulas: A review and a power study
- Semiparametric efficient estimation for shared-frailty models with doubly-censored clustered data
- Regression analysis of informative current status data with the additive hazards model
- Efficient estimation for the proportional hazards model with bivariate current status data
- Convergence rate of sieve estimates
- On methods of sieves and penalization
- Regression analysis of bivariate current status data under the gamma-frailty proportional hazards model using the EM algorithm
- Regression analysis of current status data in the presence of dependent censoring with applications to tumorigenicity experiments
- Vine copula based likelihood estimation of dependence patterns in multivariate event time data
- Weak convergence and empirical processes. With applications to statistics
- Learning causal structure from mixed data with missing values using Gaussian copula models
- The statistical analysis of interval-censored failure time data.
- On assessing the association for bivariate current status data
- Semiparametric transformation models for current status data with informative censoring
- Bayesian Models for Multivariate Current Status Data with Informative Censoring
- Bivariate current status data with univariate monitoring times
- Censored Data and the Bootstrap
- Regression analysis of bivariate current status data under the proportional hazards model
- Estimation of the mean function with panel count data using monotone polynomial splines
- Efficient Estimation of Semiparametric Multivariate Copula Models
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