Package: TFM 0.1.0

TFM: Sparse Online Principal Component for TFM

The Truncated Factor Model is a statistical model designed to handle specific data structures in data analysis. This R package focuses on the Sparse Online Principal Component Estimation method, which is used to calculate data such as the loading matrix and specific variance matrix for truncated data, thereby better explaining the relationship between common factors and original variables. Additionally, the R package also provides other equations for comparison with the Sparse Online Principal Component Estimation method.The philosophy of the package is described in Guangbao Guo. (2023) <doi:10.1007/s00180-022-01270-z>.

Authors:Beibei Wu [aut], Guangbao Guo [aut, cre]

TFM_0.1.0.tar.gz
TFM_0.1.0.zip(r-4.5)TFM_0.1.0.zip(r-4.4)TFM_0.1.0.zip(r-4.3)
TFM_0.1.0.tgz(r-4.4-any)TFM_0.1.0.tgz(r-4.3-any)
TFM_0.1.0.tar.gz(r-4.5-noble)TFM_0.1.0.tar.gz(r-4.4-noble)
TFM_0.1.0.tgz(r-4.4-emscripten)TFM_0.1.0.tgz(r-4.3-emscripten)
TFM.pdf |TFM.html✨
TFM/json (API)

# Install 'TFM' in R:
install.packages('TFM', repos = c('https://guangbaog.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 7 exports 19 dependencies

Last updated 7 days agofrom:96cd0d9dc8. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 15 2024
R-4.5-winOKNov 15 2024
R-4.5-linuxOKNov 15 2024
R-4.4-winOKNov 15 2024
R-4.4-macOKNov 15 2024
R-4.3-winOKNov 15 2024
R-4.3-macOKNov 15 2024

Exports:IPC_printPPC_printSAPC_printSOPC_PrintSPC_printTFMttestTFM

Dependencies:clielasticnetFuzzyNumbersFuzzyNumbers.Ext.2larsmagrittrMASSmatrixcalcmvtnormrbibutilsRcppRcppArmadilloRdpackrellipticalrlangRyacas0settingsSOPCxml2