# The Effect of Data Transformation on Singular Spectrum Analysis for Forecasting
## 6 Concluding Remarks
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Series’** & \multicolumn{3}{c}{**h = 1**} & \multicolumn{3}{c}{**h = 3**} \\
**Code** & **NT** & **Std** & **Log** & **NT** & **Std** & **Log** \\ \hline A001 & 1.283 & 0.542 & 1.144 & 1.884 & 1.157 & 1.715 \\ A002 & 36.275 & 35.019 & 28.844 & 36.991 & 35.900 & 30.741 \\ A003 & 12,521.688 & 13,643.067 & 13,616.737 & 16,041.250 & 16,584.228 & 17,449.138 \\ A004 & 0.250 & 0.150 & 0.139 & 0.792 & 0.354 & 0.333 \\ A005 & 61.625 & 61.548 & 60.476 & 53.906 & 53.268 & 58.074 \\ A006 & 0.068 & 0.063 & 0.067 & 0.100 & 0.107 & 0.099 \\ A007 & 338.358 & 511.055 & 288.753 & 511.033 & 560.970 & 331.925 \\ A008 & 7.129 & 5.667 & 7.505 & 19.200 & 16.096 & 17.845 \\ A009 & 0.042 & 0.040 & 0.042 & 0.051 & 0.051 & 0.051 \\ A010 & 0.122 & 0.107 & 0.155 & 0.268 & 0.306 & 0.417 \\ A011 & 0.338 & 0.229 & 0.286 & 0.831 & 0.407 & 0.560 \\ A012 & 0.984 & 0.963 & 1.049 & 1.374 & 1.410 & 1.386 \\ A013 & 1.345 & 1.101 & 1.395 & 3.141 & 2.971 & 7.484 \\ A014 & 8.096 & 6.829 & 6.410 & 9.515 & 9.810 & 9.638 \\ A015 & \(7.24\times 10^{9}\) & \(6.45\times 10^{9}\) & \(6.31\times 10^{9}\) & \(1.1\times 10^{10}\) & \(8.45\times 10^{9}\) & \(7.08\times 10^{9}\) \\ A016 & \(1.28\times 10^{10}\) & \(1.46\times 10^{10}\) & \(1.56\times 10^{10}\) & \(1.76\times 10^{10}\) & \(1.74\times 10^{10}\) & \(1.81\times 10^{10}\) \\ A017 & 12.423 & 9.066 & Inf & 19.782 & 15.435 & Inf \\ A018 & 7.950 & 8.093 & 10.205 & 15.132 & 12.983 & 16.137 \\ A019 & 1.429 & 1.425 & 1.375 & 1.531 & 1.510 & 1.469 \\ A020 & 1.319 & 1.389 & 1.669 & 1.363 & 1.482 & 1.429 \\ A021 & 1.070 & 1.076 & 1.051 & 1.129 & 1.147 & 1.122 \\ A022 & 1.133 & 1.209 & 1.152 & 1.280 & 1.270 & 1.275 \\ A023 & 6.097 & 5.936 & 5.309 & 6.551 & 6.674 & 5.980 \\ A024 & 0.959 & 0.771 & 0.954 & 1.067 & 0.971 & 1.096 \\ A025 & 22.689 & 26.924 & 56.529 & 26.056 & 43.196 & 49.542 \\ A026 & 1.174 & 1.212 & 2.490 & 1.686 & 1.787 & 3.475 \\ A027 & 0.050 & 0.100 & 0.064 & 0.114 & 0.509 & 0.226 \\ A028 & 4137.576 & 4218.129 & 4038.143 & 4474.756 & 4199.967 & 4183.622 \\ A029 & 59.124 & 44.474 & 52.390 & 62.490 & 69.349 & 78.321 \\ A030 & 15.207 & 31.175 & 16.755 & 24.388 & 51.218 & 32.464 \\ A031 & 8.783 & 5.662 & 8.633 & 80.118 & 8.464 & 18.103 \\ A032 & 9.779 & 10.315 & 9.972 & 12.431 & 13.093 & 12.748 \\ A033 & 5.820 & 5.432 & 5.791 & 9.729 & 8.527 & 10.148 \\ A034 & 3.061 & 2.785 & 3.320 & 5.796 & 5.286 & 6.157 \\ A035 & 0.965 & 1.455 & 5.973 & 1.536 & 2.155 & 6.234 \\ A036 & 0.151 & 0.175 & 0.186 & 0.169 & 0.279 & 0.249 \\ A037 & 0.293 & 0.310 & 0.308 & 0.417 & 0.395 & 0.368 \\ A038 & 1.923 & 1.243 & 3.462 & 2.427 & 1.370 & 2.474 \\ A039 & 4.853 & 3.508 & 5.107 & 7.494 & 6.099 & 9.125 \\ A040 & 489.909 & 614.577 & 717.710 & 815.463 & 785.927 & 929.787 \\ A041 & 0.329 & 0.322 & 0.328 & 0.390 & 0.408 & 0.389 \\ A042 & 68.459 & 82.182 & 67.108 & 132.417 & 212.367 & 118.468 \\ A043 & 33.081 & 33.066 & 33.750 & 41.996 & 40.189 & 43.350 \\ A044 & 420.634 & 389.750 & 545.116 & 538.590 & 552.070 & 726.264 \\ A045 & 0.522 & 0.522 & 0.886 & 0.999 & 0.998 & 1.297 \\ A046 & 15.552 & 1.906 & 1.169 & 18.721 & 5.275 & 3.773 \\ A047 & 8.206 & 8.222 & 11.116 & 8.679 & 8.640 & 10.166 \\ A048 & \(3.15\times 10^{5}\) & \(1.66\times 10^{5}\) & \(1.79\times 10^{7}\) & \(3.82\times 10^{5}\) & \(1.95\times 10^{5}\) & 595,729.790 \\ A049 & 1.189 & 1.248 & 1.199 & 1.277 & 1.377 & 1.285 \\ A050 & 18.038 & 128.254 & 17.562 & 37.219 & 295.980 & 35.731 \\ \hline \hline \end{tabular} \(\rm{NT}=No\) Transformation, Std = Standardisation, and Log = Logarithmic.  
\end{table} 
Table 3: Out-of-sample forecasting RMSFE.