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Generates Skew Factor Models data and applies Sparse Online Principal Component (SOPC) method to estimate model parameters. It includes capabilities for calculating mean squared error, relative error, and sparsity of the loading matrix. Additionally, it includes robust regression methods such as adaptive Huber regression.The philosophy of the package is described in Guo G. (2023) <doi:10.1007/s00180-022-01270-z>.
| Version: | 0.1.0 |
| Imports: | MASS, SOPC, matrixcalc, sn, stats |
| Suggests: | testthat (≥ 3.0.0), ggplot2, reshape2 |
| Published: | 2024-11-12 |
| DOI: | 10.32614/CRAN.package.SFM |
| Author: | Guangbao Guo [aut, cre], Yu Jin [aut] |
| Maintainer: | Guangbao Guo <ggb11111111 at 163.com> |
| License: | MIT + file LICENSE |
| NeedsCompilation: | no |
| Language: | en-US |
| CRAN checks: | SFM results |
| Reference manual: | SFM.pdf |
| Package source: | SFM_0.1.0.tar.gz |
| Windows binaries: | r-devel: SFM_0.1.0.zip, r-release: SFM_0.1.0.zip, r-oldrel: SFM_0.1.0.zip |
| macOS binaries: | r-release (arm64): SFM_0.1.0.tgz, r-oldrel (arm64): SFM_0.1.0.tgz, r-release (x86_64): SFM_0.1.0.tgz, r-oldrel (x86_64): SFM_0.1.0.tgz |
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