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2022 | OriginalPaper | Buchkapitel

A Robust Approach to Statistical Quality Control for High-Dimensional Non-Normal Data

verfasst von : M. Rauf Ahmad, S. Ejaz Ahmed

Erschienen in: Advances and Innovations in Statistics and Data Science

Verlag: Springer International Publishing

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Abstract

A recently proposed modification to the limit of the Hotelling’s T 2-statistic for statistical control under high-dimensional settings is evaluated for its robustness to the normality assumption. The limit, evaluated for high-dimensional asymptotics, is shown to be robust under a few mild assumptions and a general multivariate model covering normality as a special case. Further, the limit holds without any dimension reduction or preprocessing. The validity of the limit is demonstrated through simulations.

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Literatur
Zurück zum Zitat Ahmad, R. (2017). Location-invariant multi-sample U-tests for covariance matrices with large dimension. Scandinavian Journal of Statistics, 44, 500–523. Ahmad, R. (2017). Location-invariant multi-sample U-tests for covariance matrices with large dimension. Scandinavian Journal of Statistics, 44, 500–523.
Zurück zum Zitat Ahmad, R., & Ahmed, E. (2020). On the distribution of the T 2 statistic, used in statistical process monitoring, for high-dimensional data. Statistics & Probability Letters, 168, 108919.CrossRef Ahmad, R., & Ahmed, E. (2020). On the distribution of the T 2 statistic, used in statistical process monitoring, for high-dimensional data. Statistics & Probability Letters, 168, 108919.CrossRef
Zurück zum Zitat Capizzi, G., & Masarotto, G. (2017). Phase I distribution-free analysis of multivariate data. Technometrics, 59, 484–495.CrossRef Capizzi, G., & Masarotto, G. (2017). Phase I distribution-free analysis of multivariate data. Technometrics, 59, 484–495.CrossRef
Zurück zum Zitat Chen, N., Zi, X., & Zou, C. (2016). A distribution-free multivariate control chart. Technometrics, 58, 448–459.CrossRef Chen, N., Zi, X., & Zou, C. (2016). A distribution-free multivariate control chart. Technometrics, 58, 448–459.CrossRef
Zurück zum Zitat Jiang, J. (2010). Large sample techniques for statistics. New York: Springer.CrossRef Jiang, J. (2010). Large sample techniques for statistics. New York: Springer.CrossRef
Zurück zum Zitat Johnson, R. A., & Wichern, D. W. (2007). Applied multivariate statistical analysis (6th ed.). Englewood: Prentice Hall. Johnson, R. A., & Wichern, D. W. (2007). Applied multivariate statistical analysis (6th ed.). Englewood: Prentice Hall.
Zurück zum Zitat Montgomery, D. C. (2013). Statistical quality control: A modern introduction. New York: Wiley. Montgomery, D. C. (2013). Statistical quality control: A modern introduction. New York: Wiley.
Zurück zum Zitat Qiu, P. (2008). Distribution-free multivariate process control based on log-linear modeling. IIE Transactions, 40, 664–677.CrossRef Qiu, P. (2008). Distribution-free multivariate process control based on log-linear modeling. IIE Transactions, 40, 664–677.CrossRef
Zurück zum Zitat Qiu, P. (2014). Introduction to statistical process control. Boca Raton: CRC. Qiu, P. (2014). Introduction to statistical process control. Boca Raton: CRC.
Zurück zum Zitat Qiu, P. (2018). Some perspectives on nonparametric statistical process control. Journal of Quality Technology, 50, 49–65.CrossRef Qiu, P. (2018). Some perspectives on nonparametric statistical process control. Journal of Quality Technology, 50, 49–65.CrossRef
Zurück zum Zitat Qiu, P. (2019). Big data? Statistical process control can help! The American Statistician, 74(4), 329–344.CrossRef Qiu, P. (2019). Big data? Statistical process control can help! The American Statistician, 74(4), 329–344.CrossRef
Zurück zum Zitat Qiu, P., & Hawkins, D. M. (2001). A rank based multivariate CUSUM procedure. Technometrics, 43, 120–132.CrossRef Qiu, P., & Hawkins, D. M. (2001). A rank based multivariate CUSUM procedure. Technometrics, 43, 120–132.CrossRef
Zurück zum Zitat Serfling, R.J. (1980). Approximation theorems of mathematical statistics. Weinheim: Wiley.CrossRef Serfling, R.J. (1980). Approximation theorems of mathematical statistics. Weinheim: Wiley.CrossRef
Zurück zum Zitat Zou, C., Tsung, F., & Wang, Z. (2008). Monitoring profiles based on nonparametric regression methods. Technometrics, 50, 512–526.CrossRef Zou, C., Tsung, F., & Wang, Z. (2008). Monitoring profiles based on nonparametric regression methods. Technometrics, 50, 512–526.CrossRef
Metadaten
Titel
A Robust Approach to Statistical Quality Control for High-Dimensional Non-Normal Data
verfasst von
M. Rauf Ahmad
S. Ejaz Ahmed
Copyright-Jahr
2022
DOI
https://doi.org/10.1007/978-3-031-08329-7_6

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