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SAS/Ets 9.22 User's Guide 204. Provides detailed reference material for using SAS/ETS software and guides you through the analysis and forecasting of features such as univariate and multivariate time series, cross-sectional time series, seasonal adjustments, multiequational nonlinear models, discrete choice models, limited dependent variable models, portfolio analysis, and generation of financial reports, with introductory and advanced examples for each procedure. You can also find complete information about two easy-to-use point-and-click applications: the Time Series Forecasting System, for automatic and interactive time series modeling and forecasting, and the Investment Analysis System, for time-value of money analysis of a variety of investments | 2022 F Chapter 31 The UCM Procedure The sum of absolute prediction errors SAE in this holdout region are used to compare the different models. proc ucm data callCenter id datetime interval dthour6 model calls irregular level season length 28 type trig print harmonics estimate back 28 forecast back 28 lead 28 run The forecasting performance of this model in the holdout region is shown in Output 31.3.1. The sum of absolute prediction errors SAE 516.22 which appears in the last row of the holdout analysis table. Output 31.3.1 Predictions in the Holdout Region Baseline Model Obs datetime Actual Forecast Error SAE 525 24APR00 00 12 -4.004 16.004 16.004 526 24APR00 06 136 110.825 25.175 41.179 527 24APR00 12 295 262.820 32.180 73.360 528 24APR00 18 172 145.127 26.873 100.232 529 25APR00 00 20 2.188 17.812 118.044 530 25APR00 06 127 105.442 21.558 139.602 531 25APR00 12 236 217.043 18.957 158.559 532 25APR00 18 125 114.313 10.687 169.246 533 26APR00 00 16 2.855 13.145 182.391 534 26APR00 06 108 95.202 12.798 195.189 535 26APR00 12 207 194.184 12.816 208.005 536 26APR00 18 112 97.687 14.313 222.317 537 27APR00 00 15 1.270 13.730 236.047 538 27APR00 06 98 85.875 12.125 248.172 539 27APR00 12 200 184.891 15.109 263.281 540 27APR00 18 113 93.113 19.887 283.168 541 28APR00 00 15 -1.120 16.120 299.288 542 28APR00 06 104 84.983 19.017 318.305 543 28APR00 12 205 177.940 27.060 345.365 544 28APR00 18 89 64.292 24.708 370.073 545 29APR00 00 12 -6.020 18.020 388.093 546 29APR00 06 68 46.286 21.714 409.807 547 29APR00 12 116 100.339 15.661 425.468 548 29APR00 18 54 34.700 19.300 444.768 549 30APR00 00 10 -6.209 16.209 460.978 550 30APR00 06 30 12.167 17.833 478.811 551 30APR00 12 66 49.524 16.476 495.287 552 30APR00 18 61 40.071 20.929 516.216 Now that a baseline model is created the exploration for alternate models can begin. The review of the harmonic table in Output 31.3.2 shows that all but the last three harmonics are significant and deleting any of them to form a subset .
