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:Wei Liu [aut, cre], Huazhen Lin [aut], Shurong Zheng [aut], Jin Liu [aut], Jinyu Nie [aut]

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)

Peer review:

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

On CRAN:

approximate-factor-modelfeature-extractionnonlinear-dimension-reductionnumber-of-factors

7 exports 2 stars 1.82 score 11 dependencies 2 dependents 2 mentions 2 scripts 258 downloads

Last updated 23 hours agofrom:b2cff58c41. Checks:OK: 9. Indexed: yes.

Exports:chooseFacNumberFactormgendatagfmmeasurefunoverdispersedGFMOverGFMchooseFacNumber

Dependencies:codetoolsdoSNOWforeachirlbaiteratorslatticeMASSMatrixRcppRcppArmadillosnow