Simultaneous monitoring of process mean vector and covariance matrix via penalized likelihood estimation
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DOI: 10.1016/j.csda.2014.04.017
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References listed on IDEAS
- Jiahua Chen & Zehua Chen, 2008. "Extended Bayesian information criteria for model selection with large model spaces," Biometrika, Biometrika Trust, vol. 95(3), pages 759-771.
- Zhou, Qin & Luo, Yunzhao & Wang, Zhaojun, 2010. "A control chart based on likelihood ratio test for detecting patterned mean and variance shifts," Computational Statistics & Data Analysis, Elsevier, vol. 54(6), pages 1634-1645, June.
- Maboudou-Tchao, Edgard M. & Agboto, Vincent, 2013. "Monitoring the covariance matrix with fewer observations than variables," Computational Statistics & Data Analysis, Elsevier, vol. 64(C), pages 99-112.
- Zou, Changliang & Qiu, Peihua, 2009. "Multivariate Statistical Process Control Using LASSO," Journal of the American Statistical Association, American Statistical Association, vol. 104(488), pages 1586-1596.
- Jacob Bien & Robert J. Tibshirani, 2011. "Sparse estimation of a covariance matrix," Biometrika, Biometrika Trust, vol. 98(4), pages 807-820.
- Bo Li & Kaibo Wang & Arthur Yeh, 2013. "Monitoring the covariance matrix via penalized likelihood estimation," IISE Transactions, Taylor & Francis Journals, vol. 45(2), pages 132-146.
- Horowitz, Joel L & Spokoiny, Vladimir G, 2001. "An Adaptive, Rate-Optimal Test of a Parametric Mean-Regression Model against a Nonparametric Alternative," Econometrica, Econometric Society, vol. 69(3), pages 599-631, May.
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Cited by:
- Manuel Cabral Morais & Wolfgang Schmid & Patrícia Ferreira Ramos & Taras Lazariv & António Pacheco, 2019. "Comparison of joint control schemes for multivariate normal i.i.d. output," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 103(2), pages 257-287, June.
- Nishimura, Kazuya & Matsuura, Shun & Suzuki, Hideo, 2015. "Multivariate EWMA control chart based on a variable selection using AIC for multivariate statistical process monitoring," Statistics & Probability Letters, Elsevier, vol. 104(C), pages 7-13.
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More about this item
Keywords
Likelihood ratio test; L1 penalty function; Penalized likelihood estimation; Phase II monitoring;All these keywords.
JEL classification:
- L1 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance
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