Description
Robust Hotelling-Type T² Control Chart Based on the Dual STATIS Approach.
Description
Implements a robust multivariate control-chart methodology for batch-based industrial processes with multiple correlated variables using the Dual STATIS (Structuration des Tableaux A Trois Indices de la Statistique) framework. A robust compromise covariance matrix is constructed from Phase I batches with the Minimum Covariance Determinant (MCD) estimator, and a Hotelling-type T² statistic is applied for anomaly detection in Phase II. The package includes functions to simulate clean and contaminated batches, to compute both robust and classical Hotelling T² control charts, to visualize results via robust biplots, and to launch an interactive 'shiny' dashboard. An internal dataset (pharma_data) is provided for reproducibility. See Lavit, Escoufier, Sabatier and Traissac (1994) <doi:10.1016/0167-9473(94)90134-1> for the original STATIS methodology, and Rousseeuw and Van Driessen (1999) <doi:10.1080/00401706.1999.10485670> for the MCD estimator.
README.md
robustT2: Robust Hotelling-Type T2 Control Chart Based on STATIS Dual
Overview
robustT2 is an R package designed for robust multivariate statistical process control.
It implements methods based on the STATIS Dual approach to monitor batch-based industrial processes involving multiple correlated quality variables.
The package provides:
- Construction of a robust compromise covariance matrix using Minimum Covariance Determinant (MCD) estimators.
- Robust Hotelling-type T² statistics for anomaly detection.
- Phase II monitoring using standardized Mahalanobis distances projected onto the compromise structure.
- Visualization tools through robust biplots (GH-Biplot and HJ-Biplot) and an interactive Shiny dashboard.
An internal dataset (datos_farma) is included for reproducibility and demonstration.
Installation
You can install the development version directly from GitHub:
``r
install.packages("devtools")
devtools::install_github("SergioDanielFG/robustT2")
Authors
Sergio Daniel Frutos Galarza PhD Candidate in Multivariate Statistics University of Salamanca (USAL)
Contributors
Omar Ruiz Barzola
Dr. Purificación Galindo Villardón
License
MIT © 2025 Sergio Daniel Frutos Galarza.