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

Table 3

Simulation results of global and local mean squared using AR(1) with different parameters. The first half of the table displays the global mean squared error.

𝜌	I	II	III
CD
0.3	1.032684	1.031848	0.9912508
0.5	1.190477	1.142319	0.8841418
0.7	1.454564	1.417338	0.8683088
0.9	1.186370	1.117227	0.7043864
SQ
0.3	1.603859	1.070997	1.672791
0.5	1.646231	1.084239	1.700433
0.7	1.829821	1.050726	1.625967
0.9	1.981135	1.121463	1.589858
AQ
0.3	1.430155	0.8245817	1.563744
0.5	1.921071	1.3050117	1.888181
0.7	1.774816	1.0581883	1.713439
0.9	1.917869	1.5325202	1.702284
Fat tail data
0.3	1.0792571	0.9587506	0.9144366
0.5	0.9066489	0.8696987	0.7690691
0.7	1.3491463	1.2460089	0.8146345
0.9	1.5744066	1.4142226	0.7023962
mse at boundary
CD
0.3	1.959192	1.993277	1.9739248
0.5	1.698549	1.601896	1.2203974
0.7	1.161763	1.426407	0.9157507
0.9	1.647253	1.808840	1.1332881
SQ
0.3	2.045994	1.6759544	2.374387
0.5	1.891612	1.2883680	2.514418
0.7	1.714374	0.8980506	2.353474
0.9	2.196825	0.9884269	1.968370
AQ
0.3	1.796641	1.135821	2.304636
0.5	2.336372	1.676010	2.936859
0.7	1.752143	1.256421	1.807269
0.9	2.542747	2.410233	2.061829
Fat tail data
0.3	1.3175606	1.3487222	1.0755325
0.5	0.6829416	0.6869467	0.8313126
0.7	1.0077950	1.0629237	0.8260527
0.9	1.0001727	1.3372696	0.6346054