A LASSO Chart for Monitoring the Covariance Matrix

被引：26

作者：

Maboudou-Tchao, Edgard M. ^{[1
]}

Diawara, Norou ^{[2
]}

机构：

[1] Univ Cent Florida, Dept Stat, Orlando, FL 32816 USA

[2] Old Dominion Univ, Dept Math & Stat, Norfolk, VA 23529 USA

来源：

QUALITY TECHNOLOGY AND QUANTITATIVE MANAGEMENT | 2013年 / 10卷 / 01期

关键词：

Average run length (ARL); covariance matrix; multi standardization; penalized likelihood function; MULTIVARIATE PROCESS VARIABILITY; PENALIZED LIKELIHOOD; MODEL; SELECTION;

D O I：

10.1080/16843703.2013.11673310

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

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.

引用

页码：95 / 114

页数：20

共 50 条

[1] MONITORING THE COVARIANCE MATRIX WITH THE VMAX CHART
Machado, Marcela A. G.
Costa, Antonio F. B.
[J]. 14TH ISSAT INTERNATIONAL CONFERENCE ON RELIABILITY AND QUALITY IN DESIGN, PROCEEDINGS, 2008, : 100 - 104
[2] A new chart for monitoring the covariance matrix of bivariate processes
Costa, Antonio F. B.
Machado, Marcela A. G.
[J]. COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION, 2008, 37 (07) : 1453 - 1465
[3] On the multivariate progressive control chart for effective monitoring of covariance matrix
Ajadi, Jimoh Olawale
Hung, Kevin
Riaz, Muhammad
Ajadi, Nurudeen Ayobami
Mahmood, Tahir
[J]. QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL, 2021, 37 (06) : 2724 - 2737
[4] The Synthetic Control Chart Based on Two Sample Variances for Monitoring the Covariance Matrix
Machado, M. A. G.
Costa, A. F. B.
Rahim, M. A.
[J]. QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL, 2009, 25 (05) : 595 - 606
[5] A new chart based on sample variances for monitoring the covariance matrix of multivariate processes
Costa, A. F. B.
Machado, M. A. G.
[J]. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2009, 41 (7-8): : 770 - 779
[6] A control chart based on sample ranges for monitoring the covariance matrix of the multivariate processes
Costa, A. F. B.
Machado, M. A. G.
[J]. JOURNAL OF APPLIED STATISTICS, 2011, 38 (02) : 233 - 245
[7] An EWMA chart for monitoring the covariance matrix of a multivariate process based on dissimilarity index
Huwang, Longcheen
Lin, Po-Chun
Chang, Chih-Hsiang
Lin, Li-Wei
Tee, Yeu-Shiang
[J]. QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL, 2017, 33 (08) : 2089 - 2104
[8] A new chart based on sample variances for monitoring the covariance matrix of multivariate processes
A. F. B. Costa
M. A. G. Machado
[J]. The International Journal of Advanced Manufacturing Technology, 2009, 41 : 770 - 779
[9] A new bivariate control chart for monitoring the mean vector and covariance matrix simultaneously
Zhao, Yongman
Mei, Weijiang
[J]. Zhao, Yongman, 1600, Transport and Telecommunication Institute, Lomonosova street 1, Riga, LV-1019, Latvia (18): : 301 - 307
[10] A single chart with supplementary runs rules for monitoring the mean vector and the covariance matrix of multivariate processes
Costa, Antonio F. B.
Machado, Marcela A. G.
[J]. COMPUTERS & INDUSTRIAL ENGINEERING, 2013, 66 (02) : 431 - 437

← 1 2 3 4 5 →