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ALPHACLI= number
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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 1-number confidence. The default value for number is 0.05, corresponding to a 95% confidence interval.
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ALPHACLM= number
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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 1-number confidence. The default value for number is 0.05, corresponding to a 95% confidence interval.
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OUT= SAS-data-set
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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.
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CONSTANT= variable
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writes the transformed intercept to the output data set.
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LCL= name
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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.
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LCLM= name
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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.
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PREDICTED= name
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P= name
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stores the predicted values in the output data set under the name given.
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PREDICTEDM= name
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PM= name
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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.
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RESIDUAL= name
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R= name
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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.
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RESIDUALM= name
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RM= name
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requests that the residuals from the structural prediction be given.
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TRANSFORM= variables
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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.
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UCL= name
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stores the upper confidence limit for the predicted value (specified in the PREDICTED= option) in the output data set under
the name given.
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UCLM= name
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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.