Compositional data; Markov chain; VSI-MEWMA, control chart; Data Science
Abstract :
[en] In recent years, the monitoring of compositional data using control charts has been investigated in the Statistical Process Control field. In this study, we will design a Phase II Multivariate Exponentially Weighted Moving Average (MEWMA) control chart with variable sampling intervals to monitor compositional data based on isometric log-ratio transformation. The Average Time to Signal will be computed based on the Markov chain approach to investigate the performance of proposed chart. We also propose an optimal procedure to obtain the optimal control limit, smoothing constant, and out-of-control Average Time to Signal for different shift sizes and short sampling intervals. The performance of proposed chart in comparison with the standard MEWMA chart for monitoring compositional data is also provided. Finally, we end the paper with a conclusion and some recommendations for future research
Disciplines :
Quantitative methods in economics & management
Author, co-author :
Nguyen, Thi Thuy Van ; Université de Liège - ULiège > HEC Recherche > HEC Recherche: Business Analytics & Supply Chain Management ; Dong A University, Da Nang, Vietnam > International Research Institute for Artificial Intelligence and Data Science (IAD)
Heuchenne, Cédric ; Université de Liège - ULiège > HEC Liège : UER > UER Opérations : Statistique appliquée à la gestion et à l'économie
Tran, Kim Phuc; University of Lille, France > ENSAIT, GEMTEX
Language :
English
Title :
Monitoring Compositional Data using VSI MEWMA control chart
Publication date :
2022
Event name :
Internal Seminar: Anomaly Detection methods
Event organizer :
International Research Institute for Artificial Intelligence and Data Science (IAD), Dong A University
