RobPC
Robust Panel Clustering Algorithm
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>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.4 |
rolling linux/jammy R-4.5 | RobPC_1.4.tar.gz |
11.1 KiB |
1.4 |
rolling linux/noble R-4.5 | RobPC_1.4.tar.gz |
10.9 KiB |
1.4 |
rolling source/ R- | RobPC_1.4.tar.gz |
2.7 KiB |
1.4 |
latest linux/jammy R-4.5 | RobPC_1.4.tar.gz |
11.1 KiB |
1.4 |
latest linux/noble R-4.5 | RobPC_1.4.tar.gz |
10.9 KiB |
1.4 |
latest source/ R- | RobPC_1.4.tar.gz |
2.7 KiB |
1.4 |
2026-04-26 source/ R- | RobPC_1.4.tar.gz |
2.7 KiB |
1.4 |
2026-04-23 source/ R- | RobPC_1.4.tar.gz |
2.7 KiB |
1.4 |
2026-04-09 windows/windows R-4.5 | RobPC_1.4.zip |
13.7 KiB |
1.4 |
2025-04-20 source/ R- | RobPC_1.4.tar.gz |
2.7 KiB |