_            _    _        _         _
      /\ \         /\ \ /\ \     /\_\      / /\
      \_\ \       /  \ \\ \ \   / / /     / /  \
      /\__ \     / /\ \ \\ \ \_/ / /     / / /\ \__
     / /_ \ \   / / /\ \ \\ \___/ /     / / /\ \___\
    / / /\ \ \ / / /  \ \_\\ \ \_/      \ \ \ \/___/
   / / /  \/_// / /   / / / \ \ \        \ \ \
  / / /      / / /   / / /   \ \ \   _    \ \ \
 / / /      / / /___/ / /     \ \ \ /_/\__/ / /
/_/ /      / / /____\/ /       \ \_\\ \/___/ /
\_\/       \/_________/         \/_/ \_____\/
r-jointai 1.0.6
Dependencies: jags@4.3.1
Propagated dependencies: r-survival@3.7-0 r-rlang@1.1.4 r-rjags@4-16 r-mcmcse@1.5-0 r-mathjaxr@1.6-0 r-mass@7.3-61 r-future@1.34.0 r-coda@0.19-4.1
Channel: guix-cran
Location: guix-cran/packages/j.scm (guix-cran packages j)
Home page: https://nerler.github.io/JointAI/
Licenses: GPL 2+
Synopsis: Joint Analysis and Imputation of Incomplete Data
Description:

Joint analysis and imputation of incomplete data in the Bayesian framework, using (generalized) linear (mixed) models and extensions there of, survival models, or joint models for longitudinal and survival data, as described in Erler, Rizopoulos and Lesaffre (2021) <doi:10.18637/jss.v100.i20>. Incomplete covariates, if present, are automatically imputed. The package performs some preprocessing of the data and creates a JAGS model, which will then automatically be passed to JAGS <https://mcmc-jags.sourceforge.io/> with the help of the package rjags'.

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