Package: JLPM 1.0.2

Viviane Philipps

JLPM: Joint Latent Process Models

Estimation of extended joint models with shared random effects. Longitudinal data are handled in latent process models for continuous (Gaussian or curvilinear) and ordinal outcomes while proportional hazard models are used for the survival part. We propose a frequentist approach using maximum likelihood estimation. See Saulnier et al, 2022 <doi:10.1016/j.ymeth.2022.03.003>.

Authors:Viviane Philipps [aut, cre], Tiphaine Saulnier [aut], Cecile Proust-Lima [aut]

JLPM_1.0.2.tar.gz
JLPM_1.0.2.tar.gz(r-4.5-noble)JLPM_1.0.2.tar.gz(r-4.4-noble)
JLPM_1.0.2.tgz(r-4.4-emscripten)JLPM_1.0.2.tgz(r-4.3-emscripten)
JLPM.pdf |JLPM.html
JLPM/json (API)

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

Peer review:

Bug tracker:https://github.com/vivianephilipps/jlpm/issues

Uses libs:
  • fortran– Runtime library for GNU Fortran applications

fortran

1.00 score 234 downloads 1 exports 22 dependencies

Last updated 1 years agofrom:7743608648. Checks:OK: 1 NOTE: 1. Indexed: no.

TargetResultDate
Doc / VignettesOKNov 29 2024
R-4.5-linux-x86_64NOTENov 29 2024

Exports:jointLPM

Dependencies:clicodetoolsdoParallelforeachglueiteratorslatticelcmmlifecyclemagrittrmarqLevAlgMatrixmvtnormnlmenumDerivrandtoolboxrlangrngWELLstringistringrsurvivalvctrs