Introduction | Function usage | Arguments | Output object | Quick examples | MCAR example | MNAR with auxiliary variables | Inspecting convergence visually | How to cite
Package: Romeb 0.1.2
Romeb: Robust Median-Based Bayesian Growth Curve Modeling
Implements robust median-based Bayesian growth curve models that handle Missing Completely at Random (MCAR), Missing At Random (MAR), and Missing Not At Random (MNAR) missing-data mechanisms, and allow auxiliary variables. Models are fitted via 'rjags' (interface to 'JAGS') and summarized with 'coda'.
Authors:
Romeb_0.1.2.tar.gz
Romeb_0.1.2.zip(r-4.7)Romeb_0.1.2.zip(r-4.6)Romeb_0.1.2.zip(r-4.5)
Romeb_0.1.2.tgz(r-4.6-any)Romeb_0.1.2.tgz(r-4.5-any)
Romeb_0.1.2.tar.gz(r-4.7-any)Romeb_0.1.2.tar.gz(r-4.6-any)
Romeb_0.1.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
Romeb/json (API)
| # Install 'Romeb' in R: |
| install.packages('Romeb', repos = c('https://dandantang0.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/dandantang0/romeb/issues
Datasets:
- NYS - Youth Attitudes toward Deviance
Last updated from:778bc247a7. Checks:7 NOTE, 2 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | NOTE | 121 | ||
| source / vignettes | OK | 156 | ||
| linux-release-x86_64 | NOTE | 118 | ||
| macos-release-arm64 | NOTE | 76 | ||
| macos-oldrel-arm64 | NOTE | 73 | ||
| windows-devel | NOTE | 83 | ||
| windows-release | NOTE | 75 | ||
| windows-oldrel | NOTE | 75 | ||
| wasm-release | OK | 118 |
Exports:modelmodel_MNARmodel_MNAR_kRomeb
