Package: MMGFM 1.1.0
MMGFM: Multi-Study Multi-Modality Generalized Factor Model
We introduce a generalized factor model designed to jointly analyze high-dimensional multi-modality data from multiple studies by extracting study-shared and specified factors. Our factor models account for heterogeneous noises and overdispersion among modality variables with augmented covariates. We propose an efficient and speedy variational estimation procedure for estimating model parameters, along with a novel criterion for selecting the optimal number of factors. More details can be referred to Liu et al. (2024) <doi:10.48550/arXiv.2408.10542>.
Authors:
MMGFM_1.1.0.tar.gz
MMGFM_1.1.0.zip(r-4.5)MMGFM_1.1.0.zip(r-4.4)MMGFM_1.1.0.zip(r-4.3)
MMGFM_1.1.0.tgz(r-4.5-x86_64)MMGFM_1.1.0.tgz(r-4.5-arm64)MMGFM_1.1.0.tgz(r-4.4-x86_64)MMGFM_1.1.0.tgz(r-4.4-arm64)MMGFM_1.1.0.tgz(r-4.3-x86_64)MMGFM_1.1.0.tgz(r-4.3-arm64)
MMGFM_1.1.0.tar.gz(r-4.5-noble)MMGFM_1.1.0.tar.gz(r-4.4-noble)
MMGFM_1.1.0.tgz(r-4.4-emscripten)MMGFM_1.1.0.tgz(r-4.3-emscripten)
MMGFM.pdf |MMGFM.html✨
MMGFM/json (API)
| # Install 'MMGFM' in R: |
| install.packages('MMGFM', repos = c('https://feiyoung.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/feiyoung/mmgfm/issues
Last updated 5 months agofrom:b54d1164a4. Checks:1 OK, 10 WARNING. Indexed: yes.
| Target | Result | Latest binary |
|---|---|---|
| Doc / Vignettes | OK | Feb 01 2025 |
| R-4.5-win-x86_64 | WARNING | Feb 01 2025 |
| R-4.5-mac-x86_64 | WARNING | Feb 01 2025 |
| R-4.5-mac-aarch64 | WARNING | Feb 01 2025 |
| R-4.5-linux-x86_64 | WARNING | Feb 01 2025 |
| R-4.4-win-x86_64 | WARNING | Feb 01 2025 |
| R-4.4-mac-x86_64 | WARNING | Feb 01 2025 |
| R-4.4-mac-aarch64 | WARNING | Feb 01 2025 |
| R-4.3-win-x86_64 | WARNING | Feb 01 2025 |
| R-4.3-mac-x86_64 | WARNING | Feb 01 2025 |
| R-4.3-mac-aarch64 | WARNING | Jan 02 2025 |
Exports:gendata_mmgfmMMGFMselectFac.MMGFM
Dependencies:codetoolsdoSNOWforeachGFMirlbaiteratorslatticeMASSMatrixMultiCOAPRcppRcppArmadillosnow
