Analyzing Censored Factor Models
Overview
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.
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK14 OK2026-03-10
Documentation
- Help pages
- 12
- Examples that run
- 38%3 run in a plain check · 5 only when donttest examples are enabled (R CMD check --as-cran)
- Exported functions with examples
- 56%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 0%
Downloads
Dependencies
Installing CFM adds 27 packages (16 with compiled code, 19 MB of source tarballs). Heaviest: robustbase 2.2 MB, Rcpp 1.8 MB, RcppEigen 1.7 MB.
Code & Tests
Datasets
People & History
Pick two releases to compare their code metrics.
- RR 4.6.0 released · 2026-04-24
- 0.8.0Latest
- 0.7.02025-11-14 · diff ↗ ·
added 4 exports
censored_factor_model, censored_kernel_factor_model, incremental_censored_factor_model, weighted_censored_factor_model - 0.6.02025-10-22
- RR 4.5.0 released · 2025-04-11
Package metadata
- First published
- 2025-10-22
- Total releases
- 3 / 1 yrs
- License
- MIT + file LICENSE OSI
- Minimum R
- ≥ 3.5.0
- Bundled data
- 16 KB / 3 files
- Download size
- 30 KB
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