# Application of Multivariate Statistical Analysis in Process Control

## Keywords:

Principal component analysis, level of significance, T2 statistics, Q statistics, Loading matrix, Score matrix, Eigenvalues, Covariance matrix, Upper critical value## Abstract

Due to significant increase of information systems and its intensive usage in our everyday life, several problems like automatic identification of system faults, finding times of drastic change in stochastic characteristics as well as locating those characteristics, which “went out of control” need to be addressed. To solve these problems, we propose an algorithm based on multivariate statistical analysis. The algorithm is implemented with the R software environment and tested on custom metrics for Vesta server and other groups of random metrics.

## References

T. W. Anderson, An Inroduction to Multivariate Statistical Analysis, 3rd ed., Wiley series in Probability and Mathematical Statistics, 2003.

J. E. Jackson, A User’s Guide to Principal Components, Wiley series in Probability and Mathematical Statistics, 1991.

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## How to Cite

*Mathematical Problems of Computer Science*,

*44*, 145–153. Retrieved from http://mpcs.sci.am/index.php/mpcs/article/view/194

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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.