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tcv

0.1.0

Determining the Number of Factors in Poisson Factor Models via Thinning Cross-Validation

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Maintained by Zhijing WangFirst published 2025-09-231 releasesCRAN page ↗GitHub ↗

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>.

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1 releases. Pick two to compare their code metrics; R releases are shown for context.

  • R
    R 4.6.0 released · 2026-04-24
  • 0.1.0Latest
    2026-03-10 · current release

Package metadata

First published
2025-09-23
Total releases
1 / 1 yrs
License
GPL (>= 3) OSI
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