Abbreviated Journal Title
Qual. Technol. Quant. Manag.
Average run length (ARL); covariance matrix; multi standardization; penalized likelihood function; MULTIVARIATE PROCESS VARIABILITY; SUM CONTROL CHARTS; INDIVIDUAL; OBSERVATIONS; LIKELIHOOD-ESTIMATION; PENALIZED LIKELIHOOD; SAMPLE; VARIANCES; SELECTION; MODEL; Engineering, Industrial; Operations Research & Management Science; Statistics & Probability
Multivariate control charts are essential tools in multivariate statistical process control. In real applications, when a multivariate process shifts, it occurs in either location or scale. Several methods have been proposed recently to monitor the covariance matrix. Most of these methods use rational subgroups and are used to detect large shifts. In this paper, we propose a new accumulative method, based on penalized likelihood estimators, that uses individual observations and is useful to detect small and persistent shifts in a process when sparsity is present.
Quality Technology and Quantitative Management
Maboudou-Tchao, Edward M. and Diawara, Norou, "A LASSO Chart for Monitoring the Covariance Matrix" (2013). Faculty Bibliography 2010s. 4357.