An Approach to Monitoring Time Between Events When Events Are Frequent
Author:
Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-030-67856-2_16
Reference12 articles.
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2. Aslam, M., Azam, M., & Jun, C. H. (2018). A HEWMA-CUSUM control chart for the Weibull distribution. Communications in Statistics-Theory and Methods, 47(24), 5973–5985.
3. Borror, C. M., Keats, J. B., & Montgomery, D. C. (2003). Robustness of the time between events CUSUM. International Journal of Production Research, 41(15), 3435–3444.
4. Erto, P., Pallotta, G., Palumbo, B., & Mastrangelo, C. M. (2018). The performance of semi-empirical Bayesian control charts for monitoring Weibull data. Quality Technology and Quantitative Management, 15(1), 69–86.
5. Joshi, A., Karimi, S., Sparks, R., Paris, C., & MacIntyre, C. R. (2019). Survey of text-based epidemic intelligence: A computational linguistics perspective. ACM Computing Surveys (CSUR), 52(6), 1–19.
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