Research Article

Robust Wavelet Estimation to Eliminate Simultaneously the Effects of Boundary Problems, Outliers, and Correlated Noise

Table 5

Simulation results of global and mean squared using MA with different parameters. The first half of the table displays the global mean squared error.

ParameterI II III

CD
3.813.53620913.38134312.409326
2.56.4930296.2501293.902021
1.83.6324263.4763162.471782
0.81.2097911.2078041.093832

SQ
3.811.93760411.32256410.695495
2.56.6005326.2498176.266773
1.83.3200552.9382043.127264
0.81.9777521.4748122.017470

AQ
3.810.1785669.86099610.013281
2.56.4197295.8974595.992016
1.84.2554253.7153374.192729
0.82.0907311.5122782.047738

Fat data
3.813.01670012.5590239.863463
2.55.8989135.9439745.090725
1.83.0650803.0401022.481520
0.81.4365461.3665071.207752

mse at boundary

CD
3.85.5194415.3666193.964631
2.55.0207894.7241763.088903
1.83.5804163.9684041.913348
0.81.7233821.7087551.546141

SQ
3.810.19546110.4492419.949788
2.58.0988297.8556527.235322
1.85.4668195.5545644.674587
0.82.1767791.7437492.731832

AQ
3.815.19785615.22238015.307931
2.54.5917283.8991424.743319
1.82.6672872.3487813.388881
0.82.5895832.2015282.374601

Fat tail data
3.814.57605814.67173513.338548
2.53.3951243.3483103.594896
1.85.4012775.3726524.416008
0.81.209738 1.214468 1.478539