Research Article
Design of Multiple Dependent State Sampling Plan Application for COVID-19 Data Using Exponentiated Weibull Distribution
Table 1
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 | 20 | 0 | 10 | 3 | 0.9710 | 7 | 0 | 6 | 2 | 0.9690 | 3 | 0 | 2 | 1 | 0.9616 | | 4 | 20 | 0 | 10 | 3 | 0.9998 | 7 | 0 | 6 | 2 | 0.9998 | 3 | 0 | 2 | 1 | 0.9997 | | 6 | 20 | 0 | 10 | 3 | 1.0000 | 7 | 0 | 6 | 2 | 1.0000 | 3 | 0 | 2 | 1 | 1.0000 | | 8 | 20 | 0 | 10 | 3 | 1.0000 | 7 | 0 | 6 | 2 | 1.0000 | 3 | 0 | 2 | 1 | 1.0000 | | 10 | 20 | 0 | 10 | 3 | 1.0000 | 7 | 0 | 6 | 2 | 1.0000 | 3 | 0 | 2 | 1 | 1.0000 |
| | 0.10 | 2 | 35 | 0 | 1 | 1 | 0.9566 | 12 | 0 | 2 | 1 | 0.9546 | 7 | 1 | 3 | 1 | 0.9928 | | 4 | 32 | 0 | 10 | 3 | 0.9996 | 11 | 0 | 1 | 1 | 0.9997 | 4 | 0 | 1 | 1 | 0.9994 | | 6 | 32 | 0 | 10 | 3 | 1.0000 | 11 | 0 | 1 | 1 | 1.0000 | 4 | 0 | 1 | 1 | 1.0000 | | 8 | 32 | 0 | 10 | 3 | 1.0000 | 11 | 0 | 1 | 1 | 1.0000 | 4 | 0 | 1 | 1 | 1.0000 | | 10 | 32 | 0 | 10 | 3 | 1.0000 | 11 | 0 | 1 | 1 | 1.0000 | 4 | 0 | 1 | 1 | 1.0000 |
| | 0.05 | 2 | 66 | 1 | 2 | 3 | 0.9877 | 22 | 1 | 2 | 1 | 0.9873 | 8 | 1 | 3 | 1 | 0.9882 | | 4 | 42 | 0 | 10 | 2 | 0.9996 | 14 | 0 | 1 | 1 | 0.9995 | 5 | 0 | 2 | 1 | 0.9993 | | 6 | 42 | 0 | 10 | 2 | 1.0000 | 14 | 0 | 1 | 1 | 1.0000 | 5 | 0 | 2 | 1 | 1.0000 | | 8 | 42 | 0 | 10 | 2 | 1.0000 | 14 | 0 | 1 | 1 | 1.0000 | 5 | 0 | 2 | 1 | 1.0000 | | 10 | 42 | 0 | 10 | 2 | 1.0000 | 14 | 0 | 1 | 1 | 1.0000 | 5 | 0 | 2 | 1 | 1.0000 |
| | 0.01 | 2 | 93 | 1 | 2 | 1 | 0.9782 | 30 | 1 | 2 | 1 | 0.9686 | 11 | 1 | 5 | 1 | 0.9687 | | 4 | 64 | 0 | 10 | 2 | 0.9990 | 21 | 0 | 2 | 1 | 0.9992 | 7 | 0 | 2 | 1 | 0.9986 | | 6 | 64 | 0 | 10 | 2 | 1.0000 | 21 | 0 | 2 | 1 | 1.0000 | 7 | 0 | 2 | 1 | 0.9999 | | 8 | 64 | 0 | 10 | 2 | 1.0000 | 21 | 0 | 2 | 1 | 1.0000 | 7 | 0 | 2 | 1 | 1.0000 | | 10 | 64 | 0 | 10 | 2 | 1.0000 | 21 | 0 | 2 | 1 | 1.0000 | 7 | 0 | 2 | 1 | 1.0000 |
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