The X12 procedure can input the MDLINFOIN= and output the MDLINFOOUT= data sets. The structure of both of these data sets is the same. The difference is that when the MDLINFOIN= data set is read, only information relative to specifying a model is processed, whereas the MDLINFOOUT= data set contains the results of estimating a model. The X12 procedure can also read data sets that contain event definition data. The structure of these data sets is the same as in the SAS^{® }High Performance Forecasting system.
The MDLINFOIN= and MDLINFOOUT= data sets can contain the following variables:
enable the model information to be specified by BY groups. BY variables can be included in this data set that match the BY
variables used to process the series. If no BY variables are included, then the models specified by _NAME_
in the MDLINFOIN= data set apply to all BY groups in the DATA= data set.
should contain the variable name of the time series to which a particular model is to be applied. Omit the _NAME_
variable if you are specifying the same model for all series in a BY group.
specifies whether the observation contains regression or ARIMA information. The value of _MODELTYPE_
should be either REG to supply regression information or ARIMA to supply model information. If valid regression information
exists in the MDLINFOIN= data set for a BY group and series being processed, then the REGRESSION, INPUT, and EVENT statements
are ignored for that BY group and series. Likewise, if valid ARIMA model information exists in the data set, then the AUTOMDL,
ARIMA, and TRANSFORM statements are ignored. Valid values for the other variables in the data set depend on the value of the
_MODELTYPE_
variable. Although other values of _MODELTYPE_
might be permitted in other SAS procedures, PROC X12 recognizes only REG and ARIMA.
further qualifies the regression information in the observation. For _MODELTYPE_
=REG
, valid values of _MODELPART_
are INPUT, EVENT, and PREDEFINED. A value of INPUT indicates that this observation refers to the user-defined variable whose
name is given in _DSVAR_
. Likewise, a value of EVENT indicates that the observation refers to the SAS or user-defined event whose name is given in
_DSVAR_
. PREDEFINED indicates that the name given in _DSVAR_
is a predefined U.S. Census Bureau variable. If only ARIMA model information is included in the data set (that is, all observations
have _MODELTYPE_
=ARIMA
), then the _MODELPART_
variable can be omitted. For observations where _MODELTYPE_
=ARIMA
, valid values for _MODELPART_
are FORECAST, “.”, or blank.
further qualifies the regression or ARIMA information in the observation. For _MODELTYPE_
=REG
, the only valid value of _COMPONENT_
is SCALE. For _MODELTYPE_
= ARIMA
, the valid values of _COMPONENT_
are TRANSFORM, CONSTANT, NONSEASONAL, and SEASONAL. TRANSFORM indicates that the observation contains the information that
would be supplied in the TRANSFORM statement. CONSTANT is specified to control the constant term in the model. NONSEASONAL
and SEASONAL refer to the AR, MA, and differencing terms in the ARIMA model.
further qualifies the regression or ARIMA information in the observation. For _MODELTYPE_
=REG
, the value of _PARMTYPE_
is the same as the value of the USERTYPE= option in the REGRESSION statement. Since the USERTYPE= option applies only to user-defined events and variables, the value
of _PARMTYPE_
does not alter processing in observations where _MODELPART_
=PREDEFINED
. However, it is consistent to use a value for _PARMTYPE_
that matches the U.S. Census Bureau predefined variable. For the constant term in the model information, _PARMTYPE_
should be SCALE. For transformation information, the value of _PARMTYPE_
should be NONE, LOG, LOGIT, SQRT, or BOXCOX. For _MODELTYPE_
=ARIMA
, valid values of _PARMTYPE_
are AR, MA, and DIF.
specifies the variable name associated with the current observation. For _MODELTYPE_
=REG
, the value of _DSVAR_
is the name of the user-defined variable, the event, or the U.S. Census Bureau predefined variable. For _MODELTYPE_
=ARIMA
, _DSVAR_
should match the name of the series being processed. If the ARIMA model information applies to more than one series, then
_DSVAR_
can be blank or “.”, equivalently.
contains a numerical value that is used as a parameter for certain types of information. For example, the PREDEFINED=EASTER(6)
option in the REGESSION statement is implemented in the MDLINFOIN= data set by using _DSVAR_
=EASTER
and _VALUE_
=6
. For a BOXCOX transformation, _VALUE_
is set equal to the parameter value. For _COMPONENT_
=SEASONAL
, if _VALUE_
is nonmissing, then _VALUE_
is used as the seasonal period. If _VALUE_
is missing for _COMPONENT_
=SEASONAL
, then the seasonal period is determined by the interval of the series.
applies only to the AR and MA portions of the ARIMA model. The value of _FACTOR_
identifies the factor of the given AR or MA term. Therefore, the value of _FACTOR_
is the same for all observations that are related to the same factor.
identifies the degree for differencing and AR and MA lags. If _COMPONENT_
=SEASONAL
, then the value in _LAG_
is multiplied by the seasonal period indicated by the value of _VALUE_
.
contains the shift value for transfer functions. This value is not processed by PROC X12, but it might be processed by other procedures in which transfer functions can be specified.
indicates whether a parameter associated with the observation is to be estimated. For example, the NOINT option is indicated
by _COMPONENT_
=CONSTANT
with _NOEST_
=1
and _EST_
=0
. _NOEST_
=1
indicates that the value in _EST_
is a fixed value. _NOEST_
pertains to the constant term, to AR and MA parameters, and to regression parameters.
contains an initial or fixed value for a parameter associated with the observation that is to be estimated. _NOEST_
=1
indicates the value in _EST_
is a fixed value. _EST_ pertains to the constant term, to AR and MA parameters, and to regression parameters.
contains output information about estimated parameters. The variable _STDERR_
is not processed by the MDLINFOIN= data set for PROC X12. In the MDLINFOOUT= data set, _STDERR_
contains the standard error that pertains to the estimated parameter in the variable _EST_
.
contains output information about estimated parameters. The variable _TVALUE_
is not processed by the MDLINFOIN= data set for PROC X12. In the MDLINFOOUT= data set, _TVALUE_
contains the t value that pertains to the estimated parameter in the variable _EST_
.
contains output information about estimated parameters. The variable _PVALUE_
is not processed by the MDLINFOIN= data set for PROC X12. In the MDLINFOOUT= data set, _PVALUE_
contains the p-value that pertains to the estimated parameter in the variable _EST_
.
The INEVENT= data set can contain the following variables. When a variable is omitted from the data set, that variable is assumed to have the default value for all observations. The default values are specified in the list.
specifies the event variable name. _NAME_
is displayed with the case preserved. Since _NAME_
is a SAS variable name, the event can be referenced by using any case. The _NAME_
variable is required; there is no default.
specifies the class of event: SIMPLE, COMBINATION, PREDEFINED. The default for _CLASS_
is SIMPLE.
contains either a date keyword (SIMPLE EVENT), a predefined event variable name (PREDEFINED EVENT), or an event name (COMBINATION
EVENT). All _KEYNAME_
values are displayed in upper case. However, if the _KEYNAME_
value refers to an event name, then the actual name can be of mixed case. The default for _KEYNAME_
is no keyname, designated by “.”.
contains either the date timing value or the first date timing value to use in a do-list. The default for _STARTDATE_
is no date, designated by a missing value.
contains the last date timing value to use in a do-list. The default for _ENDDATE_
is no date, designated by a missing value.
contains the interval for the date do-list. The default for _DATEINTRVL_ is no interval, designated by “.”.
contains either the datetime timing value or the first datetime timing value to use in a do-list. The default for _STARTDT_
is no datetime, designated by a missing value.
contains the last datetime timing value to use in a do-list. The default for _ENDDT_ is no datetime, designated by a missing value.
contains the interval for the datetime do-list. The default for _DTINTRVL_
is no interval, designated by “.”.
contains either the observation number timing value or the first observation number timing value to use in a do-list. The
default for _STARTOBS_
is no observation number, designated by a missing value.
contains the last observation number timing value to use in a do-list. The default for _ENDOBS_
is no observation number, designated by a missing value.
contains the interval length of the observation number do-list. The default for _OBSINTRVL_
is no interval, designated by “.”.
specifies the type of event. The valid values of _TYPE_
are POINT, LS, RAMP, TR, TEMPRAMP, TC, LIN, LINEAR, QUAD, CUBIC, INV, INVERSE, LOG, and LOGARITHMIC. The default for _TYPE_
is POINT.
specifies the value for nonzero observation. The default for _VALUE_
is .
specifies the interval that defines the units for the duration values. The default for _PULSE_
is no interval, designated by “.”.
specifies the number of durations before the timing value. The default for _DUR_BEFORE_
is 0.
specifies the number of durations after the timing value. The default for _DUR_AFTER_
is 0.
determines whether the curve is GROWTH or DECAY before the timing value for _TYPE_
=RAMP
, _TYPE_
=TEMPRAMP
, and _TYPE_
=TC
. Valid values are GROWTH and DECAY. The default for _SLOPE_BEF_
is GROWTH.
determines whether the curve is GROWTH or DECAY after the timing value for _TYPE_
=RAMP
, _TYPE_
=TEMPRAMP
, and _TYPE_
=TC
. Valid values are GROWTH and DECAY. The default for _SLOPE_AFT_
is GROWTH unless _TYPE_
=TC
; then the default is DECAY.
specifies the number of _PULSE_
= intervals to shift the timing value. The shift can be positive (forward in time) or negative (backward in time). If _PULSE_
= is not specified, then the shift is in observations. The default for _SHIFT_
is .
specifies the parameter for EVENT of TYPE=TC. The default for _TCPARM_
is .
specifies the rule to use when combining events or when timing values of an event overlap. The valid values of _RULE_
are ADD, MAX, MIN, MINNZ, MINMAG, and MULT. The default for _RULE_
is ADD.
specifies the frequency interval at which the event should be repeated. If this value is missing, then the event is not periodic.
The default for _PERIOD_
is no interval, designated by “.”.
specifies the label or description for the event. If a label is not specified, then the default label value is displayed as
“.”. For events that produce dummy variables, either the user-supplied label or the default label is used. For COMPLEX events,
the _LABEL_
value is merely a description of the group of events.
The OUTSTAT= data set can contain the following variables:
sorts the statistics into BY groups. BY variables are included in this data set that match the BY variables used to process the series.
specifies the variable name of the time series to which the statistics apply.
describes the statistic that is stored in VALUE
or CVALUE
. STAT
takes on the following values:
the period of the series, 4 or 12.
the mode of the seasonal adjustment from the X11 statement. Possible values are ADD, MULT, LOGADD, and PSEUDOADD.
the beginning of the model span expressed as monyyyy for monthly series or yyyyQq for quarterly series.
the end of the model span expressed as monyyyy for monthly series or yyyyQq for quarterly series.
the number of forecast observations.
the lower sigma limit in standard deviation units.
the upper sigma limit in standard deviation units.
the Ljung-Box Q statistic of the residuals at lag 24, for monthly series. Note that lag 12 (pLBQ_12) and lag 16 (pLBQ_16) are included in the data set for quarterly series.
the stable seasonality F test value from Table D8.
the moving seasonality F test value from Table D8.
the final irregular-to-seasonal ratio from Table F 2.H.
the final seasonal moving average filter for all periods.
the residual seasonality F test value for Table D11 for the entire series.
the residual seasonality F test value for Table D11 for the last three years.
the residual seasonality F test value for Table D11.A for the entire series.
the residual seasonality F test value for Table D11.A for the last three years.
the residual seasonality F test value for Table D11.R for the entire series.
the residual seasonality F test value for Table D11.R for the last three years.
the Henderson trend moving average filter selected.
the final irregular-to-trend cycle ratio from Table F 2.H.
the standard deviation from Table E5.
the standard deviation from Table E6.
the standard deviation from Table E6.A.
months of cyclical dominance.
the overall level Q from Table F3.
Q overall level without M2 from Table F3.
indicates whether the format is numeric or character. FMT
=“NUM
” if the value is numeric and stored in the VALUE
variable. FMT
=“CHAR
” if the value is a string and stored in the CVALUE
variable.
contains the numerical value of the statistic or missing if the statistic is of type character.
contains the character value of the text statistic or blank if the statistic is of type numeric.