Package: MBRM 0.1.1
Jalmar M. F. Carrasco
MBRM: Mixed Regression Models with Generalized Log-Gamma Random Effects
Multivariate distribution derived from a Bernoulli mixed model under a marginal approach, incorporating a non-normal random intercept whose distribution is assumed to follow a generalized log-gamma (GLG) specification under a particular parameter setting. Estimation is performed by maximizing the log-likelihood using numerical optimization techniques (Lizandra C. Fabio, Vanessa Barros, Cristian Lobos, Jalmar M. F. Carrasco, Marginal multivariate approach: A novel strategy for handling correlated binary outcomes, 2025, under submission).
Authors:
MBRM_0.1.1.tar.gz
MBRM_0.1.1.tar.gz(r-4.6-arm64)MBRM_0.1.1.tar.gz(r-4.6-x86_64)MBRM_0.1.1.tar.gz(r-4.5-arm64)MBRM_0.1.1.tar.gz(r-4.5-x86_64)
MBRM_0.1.1.tgz(r-4.5-emscripten)
MBRM.pdf |MBRM.html✨
MBRM/json (API)
| # Install 'MBRM' in R: |
| install.packages('MBRM', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- Arthritis1 - Arthritis1 Dataset
- toenail - Toenail Dataset
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:3acf06f332. Checks:6 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 119 | ||
| linux-devel-x86_64 | OK | 136 | ||
| source / vignettes | OK | 184 | ||
| linux-release-arm64 | OK | 122 | ||
| linux-release-x86_64 | OK | 135 | ||
| wasm-release | OK | 107 |
Exports:envelope.MRMMRMfitrMRM
Dependencies:clicpp11dplyrfarverFormulagenericsggplot2gluegtableisobandlabelinglifecyclemagrittrpillarpkgconfigR6RColorBrewerRcpprlangS7scalestibbletidyselectutf8vctrsviridisLitewithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Arthritis1 Dataset | Arthritis1 |
| Compute simulation envelopes for MRM model | envelope.MRM |
| Fit Mixed Regression Model with Log-Gamma Random Effects | MRMfit |
| Compute the randomized quantile residuals for MRM model | residuals.MRM |
| Simulate Data from a Mixed Regression Model with GLG Random Effects | rMRM |
| toenail Dataset | toenail |
