Multivariate Regression Residual Analysis Report
The Residual Analysis Report shows how the multivariate regression model fits the historical data series. Figure 9-2 shows a sample Residual Analysis Report.
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The Residual Analysis Report shows how the multivariate regression model fits the historical data series. Figure 9-2 shows a sample Residual Analysis Report.
Figure 9-2. Residual Analysis Report
CA MICS Capacity Planner MULTIVARIATE REGRESSION FORECAST AND RESIDUAL ANALYSIS MULTIVARIATE REGRESSION BASED FORECAST OF: TOTCPUTM MODEL BASED ON INDEPENDENT ELEMENTS: TSOCPUTM BATCPUTM IMSCPUTM CICCPUTM 95% INDEPENDENT-ELEMENT PREDICTED RESIDUAL -------------PLOT OF RESIDUALS------------- CONFIDENCE DATE TOTCPUTM NAME VALUE TOTCPUTM TOTCPUTM -18723 0.0 ퟎ LIMITS ------- ---------- -------- --------- ---------- ---------- ------------------------------------------- ---------- 04JAN97 95:34:40.7 TSOCPUTM 47321 91:47:15.0 3:47:25.7 | 0ﯯ뻻ﯯ | 1:26:03.7 BATCPUTM 37461 | 0 | IMSCPUTM 118575 | 0 | CICCPUTM 60716 | 0 | | 0 | 11JAN97 91:11:54.9 TSOCPUTM 47779 90:36:08.0 0:35:46.9 | 0 | 1:20:01.3 BATCPUTM 37663 | 0 | IMSCPUTM 115851 | 0 | CICCPUTM 59529 | 0 | | 0 | 18JAN97 93:57:10.4 TSOCPUTM 49732 92:14:06.2 1:43:04.2 | 0ﯯ | 1:04:26.9 BATCPUTM 36463 | 0 | IMSCPUTM 119521 | 0 | CICCPUTM 59195 | 0 | | 0 | 25JAN97 92:25:59.9 TSOCPUTM 52382 93:46:39.6 -1:20:39.6 | -----0 | 1:02:14.1 BATCPUTM 35767 | 0 | IMSCPUTM 121372 | 0 | CICCPUTM 59275 | 0 | | 0 | 01FEB97 94:15:30.1 TSOCPUTM 52535 94:58:53.1 -0:43:22.9 | --0 | 1:03:10.5 BATCPUTM 36859 | 0 | IMSCPUTM 122859 | 0 | CICCPUTM 59992 | 0 | | 0 | 08FEB97 96:10:44.4 TSOCPUTM 54022 97:40:15.2 -1:29:30.8 | -----0 | 1:08:11.3 BATCPUTM 36984 | 0 | IMSCPUTM 126560 | 0 | CICCPUTM 61944 | 0 |
The Residual Analysis Report includes the following information:
MULTIVARIATE REGRESSION BASED FORECAST OF:
The dependent data element name that you specify on the entry screen.
MODEL BASED ON INDEPENDENT ELEMENTS:
The independent elements that you use to develop the model. This list might differ from the list of independent elements specified in the Model Analysis Report shown in Figure 9-1. This difference results from deleting proposed independent elements based on the minimum r-squared improvement criterion.
The columns of the report are discussed below:
DATE
The date ending value for the week or month represented by the observation.
Independent Element Name (TOTCPUTM)
The actual historical observations for the data element being modeled. Note that if the last two characters of the data element name are TM, the program assumes that the value is in seconds and uses a SAS TIME10.1 format for the report.
Two columns appear under the heading INDEPENDENT-ELEMENT for each independent element used in the model.
NAME
The name of the independent element.
VALUE
The value of the independent element for the interval.
The remaining columns of the report are described as follows:
PREDICTED (TOTCPUTM)
The predicted value for the dependent variable for the interval using the regression equation fit to the historical data. If the last two characters of the data element name are TM, the program assumes that the value is in seconds and uses a SAS TIME10.1 format for the report.
RESIDUAL (TOTCPUTM)
The error term in the regression equation. The residual is equal to the difference between the actual historical observation and the predicted value. The residual value for a point deleted from the modeling process is of no concern because the model was not developed to account for the observation. If the last two characters of the data element name are TM, then the program assumes that the value is in seconds and uses a SAS TIME10.1 format for the report.
PLOT OF RESIDUALS
The residual values plotted over the range from minus to plus the maximum residual value.
CONFIDENCE LIMITS
The confidence limits for the forecast. The confidence limits bound the potential error that might exist in the forecasts produced by the model. The confidence limits are a function of the independent element estimates provided, rather than monotonically increased as was the case with models developed by the Univariate Model Forecasting. If the last two characters of the data element name are TM, the program assumes that the value is in seconds and uses a SAS TIME10.1 format for the report.