Package: tcv
Type: Package
Title: Determining the Number of Factors in Poisson Factor Models via
        Thinning Cross-Validation
Version: 0.1.0
Date: 2025-09-01
Authors@R: c(person("Zhijing", "Wang", email = "wangzhijing@sjtu.edu.cn", role = c("aut", "cre")), person("Heng", "Peng", email = "hpeng@hkbu.edu.hk", role = "aut"), person("Peirong", "Xu", email = "prxu@sjtu.edu.cn", role = "aut"))
Description: 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>.
License: GPL (>= 3)
Encoding: UTF-8
Imports: stats, GFM, countsplit, irlba
LinkingTo: Rcpp, RcppArmadillo
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
SystemRequirements: C++17
RoxygenNote: 7.3.2
URL: https://github.com/Wangzhijingwzj/tcv
BugReports: https://github.com/Wangzhijingwzj/tcv/issues
NeedsCompilation: yes
Packaged: 2025-09-18 11:30:24 UTC; clswt-wangzhijing
Author: Zhijing Wang [aut, cre],
  Heng Peng [aut],
  Peirong Xu [aut]
Maintainer: Zhijing Wang <wangzhijing@sjtu.edu.cn>
Repository: CRAN
Date/Publication: 2025-09-23 07:40:02 UTC
Built: R 4.6.0; x86_64-w64-mingw32; 2025-10-07 02:39:30 UTC; windows
Archs: x64
