CopulaCenR: Copula-Based Regression Models for Multivariate Censored Data

Copula-based regression models for multivariate censored data, including bivariate right-censored data, bivariate interval-censored data, and right/interval-censored semi-competing risks data. Currently supports Clayton, Gumbel, Frank, Joe, AMH and Copula2 copula models. For marginal models, it supports parametric (Weibull, Loglogistic, Gompertz) and semiparametric (Cox and transformation) models. Includes methods for convenient prediction and plotting. Also provides a bivariate time-to-event simulation function and an information ratio-based goodness-of-fit test for copula. Method details can be found in Sun et.al (2019) Lifetime Data Analysis, Sun et.al (2021) Biostatistics, Sun et.al (2022) Statistical Methods in Medical Research, Sun et.al (2022) Biometrics, and Sun et al. (2023+) JRSSC.

Version: 1.2.3
Depends: R (≥ 3.5.0)
Imports: boot, caret, copBasic, copula, corpcor, flexsurv, foreach, icenReg, magrittr, plotly, pracma, survival, VineCopula
Published: 2023-09-23
Author: Tao Sun, Ying Ding
Maintainer: Tao Sun <sun.tao at ruc.edu.cn>
License: GPL (≥ 3)
NeedsCompilation: no
CRAN checks: CopulaCenR results

Documentation:

Reference manual: CopulaCenR.pdf

Downloads:

Package source: CopulaCenR_1.2.3.tar.gz
Windows binaries: r-devel: CopulaCenR_1.2.3.zip, r-release: CopulaCenR_1.2.3.zip, r-oldrel: CopulaCenR_1.2.3.zip
macOS binaries: r-release (arm64): CopulaCenR_1.2.3.tgz, r-oldrel (arm64): CopulaCenR_1.2.3.tgz, r-release (x86_64): CopulaCenR_1.2.3.tgz
Old sources: CopulaCenR archive

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