
ALPHACLI= number

sets the confidence limit size for the estimates of future values of the current realization of the response time series to
number, where number is less than one and greater than zero. The resulting confidence interval has 1number confidence. The default value for number is 0.05, corresponding to a 95% confidence interval.

ALPHACLM= number

sets the confidence limit size for the estimates of the structural or regression part of the model to number, where number is less than one and greater than zero. The resulting confidence interval has 1number confidence. The default value for number is 0.05, corresponding to a 95% confidence interval.

OUT= SASdataset

names the output data.
The following specifications are of the form KEYWORD=names, where KEYWORD= specifies the statistic to include in the output data set and names gives names to the variables that contain the statistics.

CONSTANT= variable

writes the transformed intercept to the output data set.

LCL= name

requests that the lower confidence limit for the predicted value (specified in the PREDICTED= option) be added to the output
data set under the name given.

LCLM= name

requests that the lower confidence limit for the structural predicted value (specified in the PREDICTEDM= option) be added
to the output data set under the name given.

PREDICTED= name


P= name

stores the predicted values in the output data set under the name given.

PREDICTEDM= name


PM= name

stores the structural predicted values in the output data set under the name given. These values are formed from only the
structural part of the model.

RESIDUAL= name


R= name

stores the residuals from the predicted values based on both the structural and time series parts of the model in the output
data set under the name given.

RESIDUALM= name


RM= name

requests that the residuals from the structural prediction be given.

TRANSFORM= variables

requests that the specified variables from the input data set be transformed by the autoregressive model and put in the output
data set. If you need to reproduce the data suitable for reestimation, you must also transform an intercept variable. To do
this, transform a variable that only takes the value 1 or use the CONSTANT= option.

UCL= name

stores the upper confidence limit for the predicted value (specified in the PREDICTED= option) in the output data set under
the name given.

UCLM= name

stores the upper confidence limit for the structural predicted value (specified in the PREDICTEDM= option) in the output data
set under the name given.
For example, the SAS statements
proc pdlreg data=a;
model y=x1 x2;
output out=b p=yhat r=resid;
run;
create an output data set named B. In addition to the input data set variables, the data set B contains the variable YHAT,
whose values are predicted values of the dependent variable Y, and RESID, whose values are the residual values of Y.