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:
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')) |
The latest version of this package failed to build. Look at thebuild logs for more information.
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 3 months agofrom:96cd0d9dc8. Checks:7 OK. Indexed: yes.
| Target | Result | Latest binary |
|---|---|---|
| Doc / Vignettes | OK | Dec 15 2024 |
| R-4.5-win | OK | Dec 15 2024 |
| R-4.5-linux | OK | Dec 15 2024 |
| R-4.4-win | OK | Dec 15 2024 |
| R-4.4-mac | OK | Dec 15 2024 |
| R-4.3-win | OK | Dec 15 2024 |
| R-4.3-mac | OK | Dec 15 2024 |
Exports:IPC_printPPC_printSAPC_printSOPC_PrintSPC_printTFMttestTFM
Dependencies:clielasticnetFuzzyNumbersFuzzyNumbers.Ext.2larsmagrittrMASSmatrixcalcmvtnormrbibutilsRcppRcppArmadilloRdpackrellipticalrlangRyacas0settingsSOPCxml2
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Incremental Principal Component Analysis | IPC IPC_print |
| Projected Principal Component Analysis | PPC PPC_print |
| Stochastic Approximation Principal Component Analysis | SAPC SAPC_print |
| Sparse Online Principal Component Analysis | SOPC SOPC_Print |
| Sparse Principal Component Analysis | SPC SPC_print |
| T-test for Truncated Factor Model | ttestTFM T_test_TFM |
| The TFM function is to generate Truncated factor model data. | TFM |
