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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>.
| Version: | 1.1.0 |
| Depends: | irlba, R (≥ 3.5.0) |
| Imports: | MASS, stats, GFM, MultiCOAP, Rcpp (≥ 1.0.10) |
| LinkingTo: | Rcpp, RcppArmadillo |
| Suggests: | knitr, rmarkdown |
| Published: | 2024-09-03 |
| DOI: | 10.32614/CRAN.package.MMGFM |
| Author: | Wei Liu [aut, cre], Qingzhi Zhong [aut] |
| Maintainer: | Wei Liu <liuwei8 at scu.edu.cn> |
| License: | GPL-3 |
| NeedsCompilation: | yes |
| CRAN checks: | MMGFM results |
| Reference manual: | MMGFM.pdf |
| Package source: | MMGFM_1.1.0.tar.gz |
| Windows binaries: | r-devel: MMGFM_1.1.0.zip, r-release: MMGFM_1.1.0.zip, r-oldrel: MMGFM_1.1.0.zip |
| macOS binaries: | r-release (arm64): MMGFM_1.1.0.tgz, r-oldrel (arm64): MMGFM_1.1.0.tgz, r-release (x86_64): MMGFM_1.1.0.tgz, r-oldrel (x86_64): MMGFM_1.1.0.tgz |
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