Abstract
In practice, quality characteristics do not always follow a normal distribution, and quality control processes sometimes generate non-normal response outcomes, including continuous non-normal data and discrete count data. Thus, achieving better results in such situations requires a new control chart derived from various types of response variables. This study proposes a procedure for monitoring response variables that uses control charts based on randomized quantile residuals obtained from a fitted regression model. Simulation studies demonstrate the performance of the proposed control charts under various situations. We illustrate the procedure using two real-data examples, based on normal and negative binomial regression models, respectively. The simulation and real-data results support our proposed procedure.
Original language | English (US) |
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Pages (from-to) | 716-729 |
Number of pages | 14 |
Journal | Applied Stochastic Models in Business and Industry |
Volume | 36 |
Issue number | 4 |
DOIs | |
State | Published - Jul 1 2020 |
Bibliographical note
Publisher Copyright:© 2020 John Wiley & Sons, Ltd.
Keywords
- control chart
- deviance residual
- randomized quantile residual
- statistical processes control