Figure 7-18 shows a sample Residual Analysis Report for the channel I/O study. The regression model that was developed using the smoothed data has a maximum of approximately 10 to 12% difference from the actual historical observations. You must expect this magnitude of residuals, while non-trivial, from a model that uses smoothing to eliminate apparent random variations from the historical data series. When viewing a Residual Analysis Report, look for obvious patterns in the unexplained data. For example, in Figure 7-18, you can see large positive residuals in the oldest and newest historical observations and large negative residuals in the middle observations. This pattern indicates that the data forms an arc around the regression line. The data is above the line initially, slides down below the line in the winter months, then rises again in April. If a pattern is identified in the residuals, you should reconsider your choice of model. In this example, a quadratic model may provide more predictive power. When more data is available, try the quadratic model and compare it to the linear model by contrasting the r-squared, F, and p values, as illustrated in Sections 7.4.2.2 through 7.4.2.4, to determine which model is better for a limited number of data points. A quadratic model may fit the data quite well but may fail to provide useful predictions for future elements, especially if relatively few historical observations are available. Therefore, it is not recommended that you use quadratic models when less than 30 historical observations are available.
CA MICS Capacity Planner UNIVARIATE MODELING RESIDUAL ANALYSIS UNIVARIATE FORECAST OF: CHAN5CNT BASED ON TIME ELEMENTS: LINEAR TRANSFORMED* PREDICTED RESIDUAL -------------PLOT OF RESIDUALS------------- CONFIDENCE DATE CHAN5CNT CHAN5CNT CHAN5CNT CHAN5CNT -195E4 0.0 +195E4 LIMITS +/- ------- ---------- ------------ ---------- ---------- ------------------------------------------- ---------- 30SEP97 11882418 . 10324734 1557683.74 | 0+++++++++++++++ | 1624240.54 30OCT97 12860633 12371525.50 10912672 1947961.05 | 0++++++++++++++++++++| 1416789.90 30NOV97 11743581 12302107.00 11500610 242971.35 | 0++ | 1221119.32 31DEC97 12510012 12126796.50 12088547 421464.66 | 0++++ | 1043874.36 29JAN98 12071368 12290690.00 12676485 -605117.03 | ------0 | 896056.61 26FEB98 12076524 12073946.00 13264423 -1187899 | ------------0 | 794269.29 31MAR98 12186976 12131750.00 13852360 -1665384 | -----------------0 | 757306.06 30APR96 14355185 13271080.50 14440298 -85113.10 | 0 | 794269.29 28MAY98 15011392 14683288.50 15028236 -16843.79 | 0 | 896056.61 30JUN98 17176448 16093920.00 15616173 1560274.52 | 0++++++++++++++++ | 1043874.36 30JUL98 17421158 17298803.00 16204111 1217046.83 | 0++++++++++++ | 1221119.32 31AUG98 18042957 17732057.50 16792049 1250908.14 | 0++++++++++++ | 1416789.90 31SEP98 . . 17379987 . | 0 | 1624240.54 31OCT98 . . 17967924 . | 0 | 1839490.02 31NOV98 . . 18555862 . | 0 | 2060095.20 31DEC98 . . 19143800 . | 0 | 2284505.07 31JAN99 . . 19731737 . | 0 | 2511700.04 31FEB99 . . 20319675 . | 0 | 2740987.65 31MAR99 . . 20907613 . | 0 | 2971883.57 31APR99 . . 21495550 . | 0 | 3204040.12 * - DATA SMOOTHED USING A GEOMETRIC MOVING AVERAGE. ALPHA = 0.50
Figure 7-18. Extended Example Residual Analysis Report
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