Control charts for dynamic process monitoring with an application to air pollution surveillance-Reference-Cited by-同舟云学术

Control charts for dynamic process monitoring with an application to air pollution surveillance

Published:2023-03-01 Issue:1 Volume:17 Page:
ISSN:1932-6157
Container-title:The Annals of Applied Statistics
language:
Short-container-title:Ann. Appl. Stat.

Author:

Xie Xiulin¹,Qiu Peihua¹

Affiliation:

1. Department of Biostatistics, University of Florida

Publisher

Institute of Mathematical Statistics

Subject

Statistics, Probability and Uncertainty,Modeling and Simulation,Statistics and Probability

Reference40 articles.

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2. HIGHAM, N. J. (1988). Computing a nearest symmetric positive semidefinite matrix. Linear Algebra Appl. 103 103–118.

3. CRESSIE, N. and WIKLE, C. K. (2011). Statistics for Spatio-Temporal Data. Wiley Series in Probability and Statistics. Wiley, Hoboken, NJ.

4. AL-RASHED, A., AL-MUTAIRI, N. and ATTAR, M. A. (2019). Air pollution analysis in Kuwait using a statistical technique (CUSUM). International Journal of Geosciences 10 254–294.

5. APLEY, D. W. and TSUNG, F. (2002). The autoregressive ${T^{2}}$ chart for monitoring univariate autocorrelated processes. J. Qual. Technol. 34 80–96.

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