Package: JLPM 1.0.3

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_1.0.3.tar.gz
JLPM_1.0.3.zip(r-4.5)JLPM_1.0.3.zip(r-4.4)JLPM_1.0.3.zip(r-4.3)
JLPM_1.0.3.tgz(r-4.5-x86_64)JLPM_1.0.3.tgz(r-4.5-arm64)JLPM_1.0.3.tgz(r-4.4-x86_64)JLPM_1.0.3.tgz(r-4.4-arm64)JLPM_1.0.3.tgz(r-4.3-x86_64)JLPM_1.0.3.tgz(r-4.3-arm64)
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JLPM.pdf |JLPM.html✨
JLPM/json (API)

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

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

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

On CRAN:

Conda:

fortran

2.78 score 252 downloads 4 exports 24 dependencies

Last updated 8 months agofrom:19a0c755d8. Checks:4 OK, 7 NOTE. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKFeb 18 2025
R-4.5-win-x86_64NOTEFeb 18 2025
R-4.5-mac-x86_64NOTEFeb 18 2025
R-4.5-mac-aarch64NOTEFeb 18 2025
R-4.5-linux-x86_64NOTEFeb 18 2025
R-4.4-win-x86_64NOTEFeb 18 2025
R-4.4-mac-x86_64NOTEFeb 18 2025
R-4.4-mac-aarch64NOTEFeb 18 2025
R-4.3-win-x86_64OKFeb 18 2025
R-4.3-mac-x86_64OKFeb 18 2025
R-4.3-mac-aarch64OKFeb 18 2025

Exports:convertjointLPMlogliksojournTime

Dependencies:clicodetoolsdoParallelforeachglueiteratorslatticelcmmlifecyclemagrittrmarqLevAlgMatrixmvtnormnlmenumDerivrandtoolboxRcpprlangrngWELLspacefillrstringistringrsurvivalvctrs