Mathematical Problems in Engineering / 2018 / Article / Tab 2

Research Article

Model Selection Approaches for Predicting Future Order Statistics from Type II Censored Data

Table 2

The corresponding bias and MSEs for different settings with model misspecification when the true distribution is SEV.

Assumed Distribution
Normal distributionExtreme Value distribution
biasMSEbiasMSEbiasMSEbiasMSE

10890.12250.1563-0.29650.1583-0.06690.0868-0.29690.1589
780.04170.1109-0.26850.1365-0.07390.0793-0.26920.1376
790.16590.2742-0.12330.1783-0.11310.1742-0.25390.2066
67-0.01550.0969-0.26870.1355-0.08640.0797-0.27020.1364
680.07100.2206-0.17250.1852-0.12870.1759-0.26350.2118
690.20750.46280.03040.3333-0.17410.2954-0.25710.3099
56-0.05320.1017-0.27670.1497-0.09130.0909-0.2780.1516
57-0.00370.2267-0.21440.2142-0.15480.202-0.28480.2367
580.08460.4086-0.05440.3325-0.21040.3158-0.28580.3299
590.21960.72790.09130.5969-0.27170.4812-0.32970.4914

2016180.31210.2071-0.07260.0498-0.04410.0543-0.17450.0747
14160.20530.1345-0.10280.0466-0.04550.0431-0.16580.0639
14180.33060.23890.10390.0949-0.07020.0961-0.13270.1031
12140.14240.1072-0.11980.0481-0.04450.0404-0.16460.0605
12160.22340.17020.04400.0791-0.07450.0868-0.1330.0925
12180.36850.31540.20980.1901-0.09490.155-0.14020.1594
10120.09670.0948-0.13600.0561-0.04960.0454-0.17180.0667
10140.16240.14580.01560.0853-0.07890.0949-0.1360.1015
10160.26670.25530.14670.1775-0.10320.1629-0.14170.1668
10180.43830.49680.31990.3774-0.13350.2516-0.16910.2546

3024270.54820.35430.07880.03300.08460.0522-0.05520.0298
21240.43510.24720.02700.02120.07170.0477-0.05730.0238
21270.54480.35620.20680.08210.0820.0574-0.00620.0386
18210.37430.19800.00030.01880.05940.0452-0.06340.0228
18240.42150.24140.11350.04780.05880.0523-0.02220.0343
18270.52500.34200.26120.11980.0650.0640.00120.0518
15180.31460.1777-0.02320.02210.03080.0473-0.08210.0289
15210.32570.18570.05750.03920.00690.0597-0.05780.0447
15240.36880.21900.14090.0693-0.00920.0766-0.05880.0667
15270.47530.32790.27590.1478-0.01850.1067-0.05980.0998

4032360.55360.34860.11410.03420.07150.0397-0.03580.0221
28320.44710.23460.05640.01830.06750.0352-0.03460.0166
28360.55510.34850.23450.08470.07420.04220.00380.0289
24280.39230.19460.02930.01440.06110.0344-0.03610.0148
24320.44710.23340.14340.04360.06660.0374-0.00060.0234
24360.55840.35370.30260.12570.080.04540.02790.0349
20240.37320.18310.01420.01490.05750.0362-0.03840.0163
20280.39290.19210.09320.03270.05880.0364-0.00590.0229
20320.44550.23720.19580.06740.06780.03920.0210.0289
20360.55260.35220.33740.15360.07620.04660.03620.0386

5040450.56050.34440.13860.03570.06860.0324-0.02040.018
35400.44840.22910.07170.01740.06110.028-0.02380.0127
35450.56000.34320.24910.08640.06980.03340.00860.0237
30350.39250.18590.04030.01270.05380.0282-0.02650.0117
30400.44690.22890.15600.04260.06170.03040.00690.0189
30450.55940.34930.31340.12710.07220.03630.02770.0283
25300.37100.17360.02420.01250.04990.0287-0.02760.0126
25350.39380.18690.10680.02960.05660.03030.00470.0184
25400.44410.23240.20150.06610.06120.03230.02170.0245
25450.56230.34680.35580.15550.07730.03770.04360.0318

6048540.56170.34380.15020.03740.06310.0267-0.01510.0148
42480.44750.22470.08010.01700.05620.024-0.01780.0107
42540.56290.34690.26190.08980.06660.02940.01390.0205
36420.39430.18020.05060.01190.05290.0232-0.0170.0097
36480.44780.22240.16300.04180.05860.02460.01030.0159
36540.56200.34440.32430.12750.06890.03120.03060.0246
30360.36900.16600.03120.01090.04480.0238-0.02020.0102
30420.39040.18050.11030.02780.05030.02510.00590.0155
30480.44720.22390.21190.06340.06060.02660.02760.0204
30540.56100.34560.36060.15710.07010.03230.04050.0273