cran. To fix this you can add URL: https://cran.r-universe.dev/tcv to the package DESCRIPTION file. See also theR-universe documentation.Package: tcv 0.1.0
tcv: Determining the Number of Factors in Poisson Factor Models via Thinning Cross-Validation
Implements methods for selecting the number of factors in Poisson factor models, with a primary focus on Thinning Cross-Validation (TCV). The TCV method is based on the 'data thinning' technique, which probabilistically partitions each count observation into training and test sets while preserving the underlying factor structure. The Poisson factor model is then fit on the training set, and model selection is performed by comparing predictive performance on the test set. This toolkit is designed for researchers working with high-dimensional count data in fields such as genomics, text mining, and social sciences. The data thinning methodology is detailed in Dharamshi et al. (2025) <doi:10.1080/01621459.2024.2353948> and Wang et al. (2025) <doi:10.1080/01621459.2025.2546577>.
Authors:
tcv_0.1.0.tar.gz
tcv_0.1.0.tar.gz(r-4.7-arm64)tcv_0.1.0.tar.gz(r-4.7-x86_64)tcv_0.1.0.tar.gz(r-4.6-arm64)tcv_0.1.0.tar.gz(r-4.6-x86_64)
tcv_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
tcv/json (API)
| # Install 'tcv' in R: |
| install.packages('tcv', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/wangzhijingwzj/tcv/issues
Last updated from:cc9e2cc362. Checks:6 OK. Indexed: no.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 119 | ||
| linux-devel-x86_64 | OK | 127 | ||
| source / vignettes | OK | 184 | ||
| linux-release-arm64 | OK | 119 | ||
| linux-release-x86_64 | OK | 123 | ||
| wasm-release | OK | 121 |
Exports:add_identifiabilitychooseFacNumber_ratiomultiDT
Dependencies:codetoolscountsplitdoSNOWforeachGFMirlbaiteratorslatticeMASSMatrixRcppRcppArmadillosnow
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Enforce Identifiability Constraints on Factor Model Components | add_identifiability |
| Estimating the Number of Factor by Eigenvalue Ratio of Natural Parameter Matrix in Generalized Factor Model. | chooseFacNumber_ratio |
| Perform Thinning Cross-Validation to Select Factor Number | multiDT |
