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 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.
Copyright © 1999 by SAS Institute Inc., Cary, NC, USA. All rights reserved.
