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The X11 Procedure |

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 only have values 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.

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