Package: gmvjoint 0.4.5

James Murray

gmvjoint: Joint Models of Survival and Multivariate Longitudinal Data

Fit joint models of survival and multivariate longitudinal data. The longitudinal data is specified by generalised linear mixed models. The joint models are fit via maximum likelihood using an approximate expectation maximisation algorithm. Bernhardt (2015) <doi:10.1016/j.csda.2014.11.011>.

Authors:James Murray [aut, cre]

gmvjoint_0.4.5.tar.gz
gmvjoint_0.4.5.tar.gz(r-4.5-noble)gmvjoint_0.4.5.tar.gz(r-4.4-noble)
gmvjoint_0.4.5.tgz(r-4.4-emscripten)gmvjoint_0.4.5.tgz(r-4.3-emscripten)
gmvjoint.pdf |gmvjoint.html✨
gmvjoint/json (API)
NEWS

# Install 'gmvjoint' in R:
install.packages('gmvjoint', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/jamesmurray7/gmvjoint/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library
Datasets:
  • PBC - Primary biliary cirrhosis data

2.30 score 20 scripts 237 downloads 9 exports 23 dependencies

Last updated 20 days agofrom:e44282881b. Checks:OK: 2. Indexed: no.

TargetResultDate
Doc / VignettesOKOct 06 2024
R-4.5-linux-x86_64OKOct 06 2024

Exports:boot.jointcond.ranefsdynPredjointparseCoxphrgenpoisROCsimDataxtable.joint

Dependencies:bootglmmTMBlatticelme4MASSMatrixmgcvminqamvtnormnlmenloptrnumDerivpracmarbibutilsRcppRcppArmadilloRcppEigenRdpackreformulasstatmodsurvivalTMBxtable