Research Article

Two-Parameter Modified Ridge-Type M-Estimator for Linear Regression Model

Table 16

Estimated MSEs of OLS, MRE, MRE, MRT, and RTMME at n = 100 and p = 7 when there is no outlier.

kSigmaRhod = 0.2d = 0.5d = 0.8

0.310.70.1750.1850.1710.1820.1710.1810.1750.1850.1710.1820.1700.1800.1750.1850.1710.1820.1690.179
0.80.2760.2930.2670.2830.2650.2810.2760.2930.2670.2830.2630.2780.2760.2930.2670.2830.2600.276
0.90.5430.5730.5010.5290.4940.5210.5430.5730.5010.5290.4830.5100.5430.5730.5010.5290.4730.499
0.996.1366.4162.9093.0552.6532.7876.1366.4162.9093.0552.3482.4686.1366.4162.9093.0552.1102.218
50.70.1500.1580.1500.1580.1500.1580.1500.1580.1500.1580.1500.1580.1500.1580.1500.1580.1500.158
0.80.2290.2420.2290.2410.2290.2410.2290.2420.2290.2410.2290.2410.2290.2420.2290.2410.2290.241
0.90.4950.5240.4940.5230.4930.5220.4950.5240.4940.5230.4930.5220.4950.5240.4940.5230.4920.521
0.995.6465.9555.3765.6695.3255.6155.6465.9555.3765.6695.2505.5375.6465.9555.3765.6695.1785.461
100.70.1560.1640.1560.1640.1560.1640.1560.1640.1560.1640.1560.1640.1560.1640.1560.1640.1560.164
0.80.2290.2430.2290.2430.2290.2430.2290.2430.2290.2430.2290.2430.2290.2430.2290.2430.2290.243
0.90.4570.4800.4560.4800.4560.4800.4570.4800.4560.4800.4560.4800.4570.4800.4560.4800.4560.479
0.995.3665.7355.3085.6725.2965.6605.3665.7355.3085.6725.2795.6415.3665.7355.3085.6725.2625.623

0.710.70.1750.1850.1670.1770.1650.1750.1750.1850.1670.1770.1630.1730.1750.1850.1670.1770.1620.171
0.80.2760.2930.2560.2710.2530.2680.2760.2930.2560.2710.2480.2620.2760.2930.2560.2710.2430.257
0.90.5430.5730.4560.4820.4430.4670.5430.5730.4560.4820.4250.4480.5430.5730.4560.4820.4090.431
0.996.1366.4161.7931.8841.5871.6676.1366.4161.7931.8841.3561.4246.1366.4161.7931.8841.1881.246
50.70.1500.1580.1490.1580.1490.1580.1500.1580.1490.1580.1490.1580.1500.1580.1490.1580.1490.158
0.80.2290.2420.2280.2410.2280.2410.2290.2420.2280.2410.2280.2410.2290.2420.2280.2410.2280.240
0.90.4950.5240.4910.5200.4910.5190.4950.5240.4910.5200.4900.5180.4950.5240.4910.5200.4880.517
0.995.6465.9555.0565.3314.9535.2235.6465.9555.0565.3314.8085.0705.6465.9555.0565.3314.6724.927
100.70.1560.1640.1560.1640.1560.1640.1560.1640.1560.1640.1550.1630.1560.1640.1560.1640.1550.163
0.80.2290.2430.2290.2430.2290.2430.2290.2430.2290.2430.2290.2430.2290.2430.2290.2430.2290.243
0.90.4570.4800.4560.4790.4560.4790.4570.4800.4560.4790.4550.4790.4570.4800.4560.4790.4550.479
0.995.3665.7355.2325.5915.2065.5635.3665.7355.2325.5915.1675.5215.3665.7355.2325.5915.1295.481

0.910.70.1750.1850.1650.1750.1630.1730.1750.1850.1650.1750.1610.1700.1750.1850.1650.1750.1590.168
0.80.2760.2930.2510.2660.2470.2620.2760.2930.2510.2660.2410.2550.2760.2930.2510.2660.2360.250
0.90.5430.5730.4370.4620.4220.4460.5430.5730.4370.4620.4020.4240.5430.5730.4370.4620.3850.406
0.996.1366.4161.5131.5891.3291.3956.1366.4161.5131.5891.1291.1836.1366.4161.5131.5890.9861.032
50.70.1500.1580.1490.1580.1490.1580.1500.1580.1490.1580.1490.1580.1500.1580.1490.1580.1490.157
0.80.2290.2420.2280.2410.2280.2410.2290.2420.2280.2410.2280.2400.2290.2420.2280.2410.2270.240
0.90.4950.5240.4900.5190.4890.5180.4950.5240.4900.5190.4880.5170.4950.5240.4900.5190.4860.515
0.995.6465.9554.9115.1784.7885.0495.6465.9554.9115.1784.6174.8685.6465.9554.9115.1784.4594.701
100.70.1560.1640.1560.1640.1550.1630.1560.1640.1560.1640.1550.1630.1560.1640.1560.1640.1550.163
0.80.2290.2430.2290.2430.2290.2430.2290.2430.2290.2430.2290.2430.2290.2430.2290.2430.2290.243
0.90.4570.4800.4560.4790.4550.4790.4570.4800.4560.4790.4550.4780.4570.4800.4560.4790.4550.478
0.995.3665.7355.1955.5515.1625.5165.3665.7355.1955.5515.1135.4645.3665.7355.1955.5515.0665.413