Research Article
Design of Multiple Dependent State Sampling Plan Application for COVID-19 Data Using Exponentiated Weibull Distribution
Table 4
Optimal parameters of the proposed MDSSP for EWD with
at 50
th percentile.
| | | a = 0.5 | a = 0.7 | a = 1.0 | n | | | m | | n | | | m | | n | | | m | |
| 0.25 | 2 | 26 | 1 | 2 | 2 | 0.9881 | 11 | 1 | 3 | 2 | 0.9911 | 5 | 1 | 2 | 1 | 0.9840 | 4 | 13 | 0 | 1 | 3 | 0.9980 | 6 | 0 | 5 | 2 | 0.9981 | 3 | 0 | 2 | 1 | 0.9981 | 6 | 13 | 0 | 1 | 3 | 0.9998 | 6 | 0 | 5 | 2 | 0.9998 | 3 | 0 | 2 | 1 | 0.9998 | 8 | 13 | 0 | 1 | 3 | 1.0000 | 6 | 0 | 5 | 2 | 1.0000 | 3 | 0 | 2 | 1 | 1.0000 | 10 | 13 | 0 | 1 | 3 | 1.0000 | 6 | 0 | 5 | 2 | 1.0000 | 3 | 0 | 2 | 1 | 1.0000 |
| 0.10 | 2 | 37 | 1 | 5 | 2 | 0.9796 | 15 | 1 | 4 | 2 | 0.9756 | 7 | 1 | 3 | 1 | 0.9725 | 4 | 22 | 0 | 10 | 2 | 0.9967 | 9 | 0 | 8 | 2 | 0.9959 | 4 | 0 | 1 | 1 | 0.9954 | 6 | 22 | 0 | 10 | 2 | 0.9997 | 9 | 0 | 8 | 2 | 0.9996 | 4 | 0 | 1 | 1 | 0.9996 | 8 | 22 | 0 | 10 | 2 | 0.9999 | 9 | 0 | 8 | 2 | 0.9999 | 4 | 0 | 1 | 1 | 0.9999 | 10 | 22 | 0 | 10 | 2 | 1.0000 | 9 | 0 | 8 | 2 | 1.0000 | 4 | 0 | 1 | 1 | 1.0000 |
| 0.05 | 2 | 45 | 1 | 11 | 2 | 0.9620 | 18 | 1 | 5 | 2 | 0.9566 | 8 | 1 | 3 | 1 | 0.9568 | 4 | 28 | 0 | 10 | 2 | 0.9947 | 11 | 0 | 1 | 2 | 0.9927 | 5 | 0 | 2 | 1 | 0.9948 | 6 | 28 | 0 | 10 | 2 | 0.9995 | 11 | 0 | 1 | 2 | 0.9990 | 5 | 0 | 2 | 1 | 0.9995 | 8 | 28 | 0 | 10 | 2 | 0.9999 | 11 | 0 | 1 | 2 | 1.0000 | 5 | 0 | 2 | 1 | 0.9999 | 10 | 28 | 0 | 10 | 2 | 1.0000 | 11 | 0 | 1 | 2 | 0.9999 | 5 | 0 | 2 | 1 | 1.0000 |
| 0.01 | 2 | 79 | 2 | 4 | 1 | 0.9817 | 32 | 2 | 3 | 1 | 0.9540 | 14 | 2 | 6 | 1 | 0.9711 | 4 | 43 | 0 | 1 | 1 | 0.9909 | 17 | 0 | 10 | 2 | 0.9863 | 7 | 0 | 2 | 1 | 0.9901 | 6 | 43 | 0 | 1 | 1 | 0.9991 | 17 | 0 | 10 | 2 | 0.9986 | 7 | 0 | 2 | 1 | 0.9990 | 8 | 43 | 0 | 1 | 1 | 0.9998 | 17 | 0 | 10 | 2 | 0.9998 | 7 | 0 | 2 | 1 | 0.9998 | 10 | 43 | 0 | 1 | 1 | 1.0000 | 17 | 0 | 10 | 2 | 0.9999 | 7 | 0 | 2 | 1 | 1.0000 |
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