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Provides generation and estimation of censored factor models for high-dimensional data with censored errors (normal, t, logistic). Includes Sparse Orthogonal Principal Components (SOPC), and evaluation metrics. Based on Guo G. (2023) <doi:10.1007/s00180-022-01270-z>.
| Version: | 0.7.0 |
| Depends: | R (≥ 3.5.0) |
| Imports: | stats, MASS, psych, matrixcalc, crch, Matrix, pracma, RSpectra, kernlab, mvtnorm, robustbase, truncnorm |
| Suggests: | testthat (≥ 3.0.0), ggplot2 |
| Published: | 2025-11-14 |
| DOI: | 10.32614/CRAN.package.CFM |
| Author: | Guangbao Guo [aut, cre], Tong Meng [aut] |
| Maintainer: | Guangbao Guo <ggb11111111 at 163.com> |
| License: | MIT + file LICENSE |
| NeedsCompilation: | no |
| Language: | en-US |
| CRAN checks: | CFM results |
| Reference manual: | CFM.html , CFM.pdf |
| Package source: | CFM_0.7.0.tar.gz |
| Windows binaries: | r-devel: CFM_0.6.0.zip, r-release: CFM_0.6.0.zip, r-oldrel: CFM_0.6.0.zip |
| macOS binaries: | r-release (arm64): CFM_0.6.0.tgz, r-oldrel (arm64): CFM_0.6.0.tgz, r-release (x86_64): CFM_0.7.0.tgz, r-oldrel (x86_64): CFM_0.7.0.tgz |
| Old sources: | CFM archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.