Package: RMFM 1.1.0
RMFM: Robust Matrix Factor Model
We introduce a robust matrix factor model that explicitly incorporates tail behavior and employs a mean-shift term to avoid efficiency losses through pre-centering of observed matrices. More details on the methods related to our paper are currently under submission. A full reference to the paper will be provided in future versions once the paper is published.
Authors:
RMFM_1.1.0.tar.gz
RMFM_1.1.0.tar.gz(r-4.5-noble)RMFM_1.1.0.tar.gz(r-4.4-noble)
RMFM_1.1.0.tgz(r-4.4-emscripten)RMFM_1.1.0.tgz(r-4.3-emscripten)
RMFM.pdf |RMFM.html✨
RMFM/json (API)
# Install 'RMFM' in R: |
install.packages('RMFM', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 18 days agofrom:ed58acdc6c. Checks:OK: 2. Indexed: no.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 26 2024 |
R-4.5-linux-x86_64 | OK | Nov 26 2024 |
Exports:ER.RMFMgendata_rmfmRMFM
Dependencies:CholWishartCOAPglueirlbaLaplacesDemonlatticeMASSMatrixMixMatrixRcppRcppArmadillo
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Select the structure dimension of factor matrix | ER.RMFM |
Generate simulated data | gendata_rmfm |
Fit the high-dimensional robust matrix factor model | RMFM |