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Performs both classical and robust panel clustering by applying Principal Component Analysis (PCA) for dimensionality reduction and clustering via standard K-Means or Trimmed K-Means. The method is designed to ensure stable and reliable clustering, even in the presence of outliers. Suitable for analyzing panel data in domains such as economic research, financial time-series, healthcare analytics, and social sciences. The package allows users to choose between classical K-Means for standard clustering and Trimmed K-Means for robust clustering, making it a flexible tool for various applications. For this package, we have benefited from the studies Rencher (2003), Wang and Lu (2021) <doi:10.25236/AJBM.2021.031018>, Cuesta-Albertos et al. (1997) <https://www.jstor.org/stable/2242558?seq=1>.
| Version: | 1.4 |
| Depends: | R (≥ 4.0) |
| Imports: | stats, trimcluster |
| Published: | 2025-02-20 |
| DOI: | 10.32614/CRAN.package.RobPC |
| Author: | Hasan Bulut [aut, cre] |
| Maintainer: | Hasan Bulut <hasan.bulut at omu.edu.tr> |
| License: | GPL-2 |
| NeedsCompilation: | no |
| CRAN checks: | RobPC results |
| Reference manual: | RobPC.pdf |
| Package source: | RobPC_1.4.tar.gz |
| Windows binaries: | r-devel: not available, r-release: not available, r-oldrel: RobPC_1.4.zip |
| macOS binaries: | r-devel (arm64): RobPC_1.4.tgz, r-release (arm64): RobPC_1.4.tgz, r-oldrel (arm64): RobPC_1.4.tgz, r-devel (x86_64): RobPC_1.4.tgz, r-release (x86_64): RobPC_1.4.tgz, r-oldrel (x86_64): RobPC_1.4.tgz |
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