Package: CopulaCenR
Type: Package
Title: Copula-Based Regression Models for Multivariate Censored Data
Version: 1.2.4
Authors@R: 
  c(person(given = "Tao",
           family = "Sun",
           role = c("aut", "cre"),
           email = "sun.tao@ruc.edu.cn",
           comment = c(ORCID = "0000-0003-4447-3005")),
    person(given = "Ying",
           family = "Ding",
           role = "aut",
           comment = c(ORCID = "0000-0003-1352-1000")))
Description: 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.
License: GPL (>= 3)
Imports: boot, caret, copBasic, copula, corpcor, flexsurv, foreach,
        icenReg, magrittr, plotly, pracma, survival, VineCopula
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.2.0
NeedsCompilation: no
Packaged: 2026-07-06 07:47:26 UTC; root
Author: Tao Sun [aut, cre] (<https://orcid.org/0000-0003-4447-3005>),
        Ying Ding [aut] (<https://orcid.org/0000-0003-1352-1000>)
Maintainer: Tao Sun <sun.tao@ruc.edu.cn>
Config/pak/sysreqs: cmake make libgsl0-dev libicu-dev libuv1-dev
        libssl-dev
Repository: https://suntaojj.r-universe.dev
Date/Publication: 2024-11-14 16:50:02 UTC
RemoteUrl: https://github.com/cran/CopulaCenR
RemoteRef: HEAD
RemoteSha: fdfcb5f390ddffd62ae5ebf7aa1195ae78c0ad68