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RobPC  

Robust Panel Clustering Algorithm
View on CRAN: Click here


Download and install RobPC package within the R console
Install from CRAN:
install.packages("RobPC")

Install from Github:
library("remotes")
install_github("cran/RobPC")

Install by package version:
library("remotes")
install_version("RobPC", "1.4")



Attach the package and use:
library("RobPC")
Maintained by
Hasan Bulut
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2025-02-20
Latest Update: 2025-02-20
Description:
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>.
How to cite:
Hasan Bulut (2025). RobPC: Robust Panel Clustering Algorithm. R package version 1.4, https://cran.r-project.org/web/packages/RobPC. Accessed 24 Oct. 2026.
Previous versions and publish date:
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Complete documentation for RobPC
Functions, R codes and Examples using the RobPC R package
Full RobPC package functions and examples
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