Package: GFM 1.2.1
Wei Liu
GFM: Generalized Factor Model
Generalized factor model is implemented for ultra-high dimensional data with mixed-type variables. Two algorithms, variational EM and alternate maximization, are designed to implement the generalized factor model, respectively. The factor matrix and loading matrix together with the number of factors can be well estimated. This model can be employed in social and behavioral sciences, economy and finance, and genomics, to extract interpretable nonlinear factors. More details can be referred to Wei Liu, Huazhen Lin, Shurong Zheng and Jin Liu. (2021) <doi:10.1080/01621459.2021.1999818>.
Authors:
GFM_1.2.1.tar.gz
GFM_1.2.1.zip(r-4.5)GFM_1.2.1.zip(r-4.4)GFM_1.2.1.zip(r-4.3)
GFM_1.2.1.tgz(r-4.4-x86_64)GFM_1.2.1.tgz(r-4.4-arm64)GFM_1.2.1.tgz(r-4.3-x86_64)GFM_1.2.1.tgz(r-4.3-arm64)
GFM_1.2.1.tar.gz(r-4.5-noble)GFM_1.2.1.tar.gz(r-4.4-noble)
GFM_1.2.1.tgz(r-4.4-emscripten)GFM_1.2.1.tgz(r-4.3-emscripten)
GFM.pdf |GFM.html✨
GFM/json (API)
# Install 'GFM' in R: |
install.packages('GFM', repos = c('https://feiyoung.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/feiyoung/gfm/issues
approximate-factor-modelfeature-extractionnonlinear-dimension-reductionnumber-of-factors
Last updated 2 months agofrom:b2cff58c41. Checks:OK: 9. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 16 2024 |
R-4.5-win-x86_64 | OK | Nov 16 2024 |
R-4.5-linux-x86_64 | OK | Nov 16 2024 |
R-4.4-win-x86_64 | OK | Nov 16 2024 |
R-4.4-mac-x86_64 | OK | Nov 16 2024 |
R-4.4-mac-aarch64 | OK | Nov 16 2024 |
R-4.3-win-x86_64 | OK | Nov 16 2024 |
R-4.3-mac-x86_64 | OK | Nov 16 2024 |
R-4.3-mac-aarch64 | OK | Nov 16 2024 |
Exports:chooseFacNumberFactormgendatagfmmeasurefunoverdispersedGFMOverGFMchooseFacNumber
Dependencies:codetoolsdoSNOWforeachirlbaiteratorslatticeMASSMatrixRcppRcppArmadillosnow
GFM: A Simple Transcriptomics Data
Rendered fromGFM.Brain.Rmd
usingknitr::rmarkdown
on Nov 16 2024.Last update: 2023-08-11
Started: 2021-12-25
GFM: alternate maximization and information criterion
Rendered fromGFM.Simu.Rmd
usingknitr::rmarkdown
on Nov 16 2024.Last update: 2023-08-11
Started: 2021-12-25
Installation
Rendered fromRGFM.Rmd
usingknitr::rmarkdown
on Nov 16 2024.Last update: 2023-08-11
Started: 2021-12-25
OverGFM: simulated examples
Rendered fromOverGFM_exam.Rmd
usingknitr::rmarkdown
on Nov 16 2024.Last update: 2023-08-11
Started: 2023-08-11
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Choose the Number of factors for Generalized Factor Models | chooseFacNumber |
Factor Analysis Model | Factorm |
Generate simulated data | gendata |
Generalized Factor Model | gfm |
Assess the performance of an estimator on a matrix | measurefun |
Overdispersed Generalized Factor Model | overdispersedGFM |
Choose the Number of factors for Overdispersed Generalized Factor Models | OverGFMchooseFacNumber |