Research Article
An Exponential-Cum-Sine-Type Hybrid Imputation Technique for Missing Data
Table 12
Values of bias when
and response rates are
for data generated from normal, Gamma, and Poisson distributions.
| | Bias of the proposed estimator when response rate is | | 75% | 80% | 85% | 90% | 95% |
| | | When data is generated from normal distribution | | 0.1 | −0.000 095 000 0 | −0.000 092 000 0 | −0.000 090 000 0 | −0.000 088 000 0 | −0.000 086 000 0 | | 0.2 | −0.000 093 000 0 | −0.000 088 000 0 | −0.000 083 000 0 | −0.000 078 000 0 | −0.000 075 000 0 | | 0.3 | −0.000 121 000 0 | −0.000 114 000 0 | −0.000 108 000 0 | −0.000 102 000 0 | −0.000 097 000 0 | | 0.4 | −0.000 114 000 0 | −0.000 104 000 0 | −0.000 096 000 0 | −0.000 089 000 0 | −0.000 082 000 0 | | 0.5 | −0.000 126 000 0 | −0.000 113 000 0 | −0.000 101 000 0 | −0.000 091 000 0 | −0.000 082 000 0 | | 0.6 | −0.000 135 000 0 | −0.000 120 000 0 | −0.000 106 000 0 | −0.000 094 000 0 | −0.000 083 000 0 | | 0.7 | −0.000 143 000 0 | −0.000 126 000 0 | −0.000 111 000 0 | −0.000 098 000 0 | −0.000 086 000 0 | | 0.8 | −0.000 154 000 0 | −0.000 133 000 0 | −0.000 115 000 0 | −0.000 099 000 0 | −0.000 084 000 0 | | 0.9 | −0.000 159 000 0 | −0.000 136 000 0 | −0.000 115 000 0 | −0.000 097 000 0 | −0.000 081 000 0 |
| | | When data is generated from Gamma distribution | | 0.1 | −0.000 030 580 0 | −0.000 030 510 0 | −0.000 030 460 0 | −0.000 030 400 0 | −0.000 030 360 0 | | 0.2 | −0.000 026 300 0 | −0.000 026 150 0 | −0.000 026 020 0 | −0.000 025 900 0 | −0.000 025 800 0 | | 0.3 | −0.000 030 400 0 | −0.000 030 190 0 | −0.000 030 010 0 | −0.000 029 840 0 | −0.000 029 690 0 | | 0.4 | −0.000 027 760 0 | −0.000 027 420 0 | −0.000 027 110 0 | −0.000 026 840 0 | −0.000 026 600 0 | | 0.5 | −0.000 027 550 0 | −0.000 027 110 0 | −0.000 026 730 0 | −0.000 026 390 0 | −0.000 026 080 0 | | 0.6 | −0.000 032 820 0 | −0.000 032 170 0 | −0.000 031 590 0 | −0.000 031 080 0 | −0.000 030 620 0 | | 0.7 | −0.000 029 350 0 | −0.000 028 530 0 | −0.000 027 810 0 | −0.000 027 170 0 | −0.000 026 590 0 | | 0.8 | −0.000 031 190 0 | −0.000 030 150 0 | −0.000 029 230 0 | −0.000 028 420 0 | −0.000 027 690 0 | | 0.9 | −0.000 034 810 0 | −0.000 033 330 0 | −0.000 032 030 0 | −0.000 030 880 0 | −0.000 029 850 0 |
| | | When data is generated from Poisson distribution | | 0.1 | −0.000 000 403 0 | −0.000 000 395 0 | −0.000 000 387 0 | −0.000 000 381 0 | −0.000 000 375 0 | | 0.2 | −0.000 000 447 0 | −0.000 000 430 0 | −0.000 000 415 0 | −0.000 000 402 0 | −0.000 000 390 0 | | 0.3 | −0.000 000 455 0 | −0.000 000 431 0 | −0.000 000 411 0 | −0.000 000 392 0 | −0.000 000 376 0 | | 0.4 | −0.000 000 510 0 | −0.000 000 473 0 | −0.000 000 440 0 | −0.000 000 411 0 | −0.000 000 385 0 | | 0.5 | −0.000 000 552 0 | −0.000 000 503 0 | −0.000 000 460 0 | −0.000 000 421 0 | −0.000 000 387 0 | | 0.6 | −0.000 000 632 0 | −0.000 000 568 0 | −0.000 000 511 0 | −0.000 000 461 0 | −0.000 000 416 0 | | 0.7 | −0.000 000 703 0 | −0.000 000 620 0 | −0.000 000 547 0 | −0.000 000 483 0 | −0.000 000 425 0 | | 0.8 | −0.000 000 777 0 | −0.000 000 675 0 | −0.000 000 585 0 | −0.000 000 505 0 | −0.000 000 434 0 | | 0.9 | −0.000 000 871 0 | −0.000 000 746 0 | −0.000 000 635 0 | −0.000 000 536 0 | −0.000 000 448 0 |
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