The X11 Procedure
- Overview
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Getting Started
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Syntax
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Details
Historical Development of X-11 Implementation of the X-11 Seasonal Adjustment Method Computational Details for Sliding Spans Analysis Data Requirements Missing Values Prior Daily Weights and Trading-Day Regression Adjustment for Prior Factors The YRAHEADOUT Option Effect of Backcast and Forecast Length Details of Model Selection OUT= Data Set The OUTSPAN= Data Set OUTSTB= Data Set OUTTDR= Data Set Printed Output ODS Table Names
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Examples
- References
| OUTTDR= Data Set |
The trading-day regression results (tables B15 and C15) are written to the OUTTDR= data set, which contains the following variables:
VARNAME, a character variable containing the name of the VAR variable being processed
TABLE, a character variable containing the name of the table. It can have only the value B15 (Preliminary Trading-Day Regression) or C15 (Final Trading-Day Regression).
_TYPE_, a character variable whose value distinguishes the three distinct table format types. These types are (a) the regression, (b) the listing of the standard error associated with length-of-month, and (c) the analysis of variance. The first seven observations in the OUTTDR data set correspond to the regression on days of the week; thus the _TYPE_ variable is given the value "REGRESS" (day-of-week regression coefficient). The next four observations correspond to 31-, 30-, 29-, and 28-day months and are given the value _TYPE_=LOM_STD (length-of-month standard errors). Finally, the last three observations correspond to the analysis of variance table, and _TYPE_=ANOVA.
PARM, a character variable, further identifying the nature of the observation. PARM is set to blank for the three _TYPE_=ANOVA observations.
SOURCE, a character variable containing the source in the regression. This variable is missing for all _TYPE_=REGRESS and LOM_STD.
CWGT, a numeric variable containing the combined trading-day weight (prior weight + weight found from regression). The variable is missing for all _TYPE_=LOM_STD and _TYPE_=ANOVA.
PRWGT, a numeric variable containing the prior weight. The prior weight is 1.0 if PDWEIGHTS are not specified. This variable is missing for all _TYPE_=LOM_STD and _TYPE_=ANOVA.
COEFF, a numeric variable containing the calculated regression coefficient for the given day. This variable is missing for all _TYPE_=LOM_STD and _TYPE_=ANOVA.
STDERR, a numeric variable containing the standard errors. For observations with _TYPE_=REGRESS, this is the standard error corresponding to the regression coefficient. For observations with _TYPE_=LOM_STD, this is standard error for the corresponding length-of-month. This variable is missing for all _TYPE_=ANOVA.
T1, a numeric variable containing the t statistic corresponding to the test that the combined weight is different from the prior weight. This variable is missing for all _TYPE_=LOM_STD and _TYPE_=ANOVA.
T2, a numeric variable containing the t statistic corresponding to the test that the combined weight is different from 1.0. This variable is missing for all _TYPE_=LOM_STD and _TYPE_=ANOVA.
PROBT1, a numeric variable containing the significance level for t statistic T1. The variable is missing for all _TYPE_=LOM_STD and _TYPE_=ANOVA.
PROBT2, a numeric variable containing the significance level for t statistic T2. The variable is missing for all _TYPE_=LOM_STD and _TYPE_=ANOVA.
SS, a numeric variable containing the sum of squares associated with the corresponding source term. This variable is missing for all _TYPE_=REGRESS and LOM_STD.
DF, a numeric variable containing the degrees of freedom associated with the corresponding source term. This variable is missing for all _TYPE_=REGRESS and LOM_STD.
MS, a numeric variable containing the mean square associated with the corresponding source term. This variable is missing for the source term 'Total' and for all _TYPE_=REGRESS and LOM_STD.
F, a numeric variable containing the F statistic for the 'Regression' source term. The variable is missing for the source terms 'Total' and 'Error', and for all _TYPE_=REGRESS and LOM_STD.
PROBF, a numeric variable containing the significance level for the F statistic. This variable is missing for the source term 'Total' and 'Error' and for all _TYPE_=REGRESS and LOM_STD.