Package: MultiRFM 1.1.0

Wei Liu

MultiRFM: High-Dimensional Multi-Study Robust Factor Model

We introduce a high-dimensional multi-study robust factor model, which learns latent features and accounts for the heterogeneity among source. It could be used for analyzing heterogeneous RNA sequencing data. More details can be referred to Jiang et al. (2025) <doi:10.48550/arXiv.2506.18478>.

Authors:Wei Liu [aut, cre], Xiaolu Jiang [aut]

MultiRFM_1.1.0.tar.gz
MultiRFM_1.1.0.zip(r-4.7-x86_64)MultiRFM_1.1.0.zip(r-4.6-x86_64)MultiRFM_1.1.0.zip(r-4.5-x86_64)
MultiRFM_1.1.0.tgz(r-4.6-x86_64)MultiRFM_1.1.0.tgz(r-4.6-arm64)MultiRFM_1.1.0.tgz(r-4.5-x86_64)MultiRFM_1.1.0.tgz(r-4.5-arm64)
MultiRFM_1.1.0.tar.gz(r-4.7-arm64)MultiRFM_1.1.0.tar.gz(r-4.7-x86_64)MultiRFM_1.1.0.tar.gz(r-4.6-arm64)MultiRFM_1.1.0.tar.gz(r-4.6-x86_64)
MultiRFM_1.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
MultiRFM/json (API)

# Install 'MultiRFM' in R:

install.packages('MultiRFM', repos = c('https://feiyoung.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/feiyoung/multirfm/issues

Uses libs:

openblas– Optimized BLAS
c++– GNU Standard C++ Library v3
openmp– GCC OpenMP (GOMP) support library

On CRAN:

openblas cpp openmp

2.70 score 249 downloads 3 exports 76 dependencies

Last updated from:824fae135d. Checks:11 WARNING, 1 ERROR, 1 OK. Indexed: yes.

Target	Result	Time
linux-devel-arm64	WARNING	174
linux-devel-x86_64	WARNING	192
source / vignettes	ERROR	230
linux-release-arm64	WARNING	209
linux-release-x86_64	WARNING	199
macos-release-arm64	WARNING	129
macos-release-x86_64	WARNING	266
macos-oldrel-arm64	WARNING	125
macos-oldrel-x86_64	WARNING	267
windows-devel	WARNING	184
windows-release	WARNING	179
windows-oldrel	WARNING	184
wasm-release	OK	160

Exports:gendata_simu_multi MultiRFM selectFac.MultiRFM

Dependencies:askpass base64enc bslib cachem cli cpp11 crosstalk curl data.table digest dplyr evaluate farver fastmap fontawesome fs generics ggplot2 glue gtable highr htmltools htmlwidgets httr irlba isoband jquerylib jsonlite kernlab knitr labeling LaplacesDemon later lattice lazyeval lifecycle magrittr MASS Matrix memoise mime mixtools mvtnorm nlme openssl otel pillar pkgconfig plotly promises purrr R6 rappdirs RColorBrewer Rcpp RcppArmadillo rlang rmarkdown S7 sass scales segmented stringi stringr survival sys tibble tidyr tidyselect tinytex utf8 vctrs viridisLite withr xfun yaml

Vignettes and/or manual for this package failed to build, some documents may be unavailable. Please inspect thebuild logs for more information.

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Generate Simulated Multi-Study Factor Analysis Data	gendata_simu_multi
Fit the high-dimensional multi-study robust factor model	MultiRFM
Select the number of factors	selectFac.MultiRFM