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'))

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

On CRAN:

Conda:

openblascppopenmp

1.70 score 305 downloads 9 exports 23 dependencies

Last updated 5 months agofrom:e44282881b. Checks:3 OK. Indexed: no.

TargetResultLatest binary
Doc / VignettesOKMar 05 2025
R-4.5-linux-x86_64OKMar 05 2025
R-4.4-linux-x86_64OKMar 05 2025

Exports:boot.jointcond.ranefsdynPredjointparseCoxphrgenpoisROCsimDataxtable.joint

Dependencies:bootglmmTMBlatticelme4MASSMatrixmgcvminqamvtnormnlmenloptrnumDerivpracmarbibutilsRcppRcppArmadilloRcppEigenRdpackreformulasstatmodsurvivalTMBxtable