Package: FastJM
Type: Package
Title: Semi-Parametric Joint Modeling of Longitudinal and Survival Data
Version: 1.5.2
Date: 2025-10-18
Authors@R: c(
    person("Shanpeng", "Li", email = "lishanpeng0913@ucla.edu", 
        role = c("aut", "cre")),
    person("Ning", "Li", email = "liningpv@gmail.com", 
        role = "ctb"),
    person("Hong", "Wang", email = "wh@csu.edu.cn", 
        role = "ctb"),
    person("Jin", "Zhou", email = "jinjinzhou@g.ucla.edu", 
        role = "ctb"),       
    person("Hua", "Zhou", email = "huazhou@ucla.edu", 
        role = "ctb"),
    person("Gang", "Li", email = "vli@ucla.edu", 
        role = "ctb")
    )
Maintainer: Shanpeng Li <lishanpeng0913@ucla.edu>
Encoding: UTF-8
Description: Maximum likelihood estimation for the semi-parametric joint modeling of competing risks and (multivariate) longitudinal data applying customized linear scan algorithms, proposed by Li and colleagues (2022) <doi:10.1155/2022/1362913>. 
             The time-to-event data is modelled using a (cause-specific) Cox proportional hazards regression model with time-fixed covariates. The longitudinal 
             outcome is modelled using a linear mixed effects model. The association is captured by shared random effects. The model 
             is estimated using an Expectation Maximization algorithm.
License: GPL (>= 3)
NeedsCompilation: yes
Imports: Rcpp (>= 1.0.7), dplyr, nlme, caret, timeROC, future,
        future.apply
LinkingTo: Rcpp, RcppEigen
Depends: R (>= 3.5.0), survival, utils, MASS, statmod, magrittr
RoxygenNote: 7.3.2
LazyData: true
Packaged: 2025-10-18 04:09:31 UTC; shanpengli
Suggests: testthat (>= 3.0.0), spelling
Language: en-US
Config/testthat/edition: 3
Author: Shanpeng Li [aut, cre],
  Ning Li [ctb],
  Hong Wang [ctb],
  Jin Zhou [ctb],
  Hua Zhou [ctb],
  Gang Li [ctb]
Repository: CRAN
Date/Publication: 2025-10-18 06:10:14 UTC
Built: R 4.4.3; x86_64-w64-mingw32; 2025-11-01 06:06:35 UTC; windows
Archs: x64
