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SAS Macros and Functions

Syntax

The form of the %BOXCOXAR macro is

%BOXCOXAR (SAS-data-set, variable [ , options ] )
The first argument, SAS-data-set, specifies the name of the SAS data set containing the time series to be analyzed. The second argument, variable, specifies the time series variable name to be analyzed. The first two arguments are required.

The following options can be used with the %BOXCOXAR macro. Options must follow the required arguments and are separated by commas.

AR= n
specifies the order of the autoregressive model fit to the transformed series. The default is AR=5.

CONST= value
specifies a constant c to be added to the series before transformation. Use the CONST= option when some values of the series are 0 or negative. The default is CONST=0.

DIF= ( differencing-list )
specifies the degrees of differencing to apply to the transformed series before the autoregressive model is fit. The differencing-list is a list of positive integers separated by commas and enclosed in parentheses. For example, DIF=(1,12) specifies that the transformed series be differenced once at lag 1 and once at lag 12. For more details, see "IDENTIFY Statement" in Chapter 7, "The ARIMA Procedure,".

LAMBDAHI= value
specifies the maximum value of lambda for the grid search. The default is LAMBDAHI=1. A large (in magnitude) LAMBDAHI= value can result in problems with floating point arithmetic.

LAMBDALO= value
specifies the minimum value of lambda for the grid search. The default is LAMBDALO=0. A large (in magnitude) LAMBDALO= value can result in problems with floating point arithmetic.

NLAMBDA= value
specifies the number of lambda values considered, including the LAMBDALO= and LAMBDAHI= option values. The default is NLAMBDA=2.

OUT= SAS-data-set
writes the results to an output data set. The output data set includes the lambda values tried (LAMBDA), and for each lambda value the log likelihood (LOGLIK), residual mean square error (RMSE), Akaike Information Criterion (AIC), and Schwarz's Bayesian Criterion (SBC).

PRINT= YES | NO
specifies whether results are printed. The default is PRINT=YES. The printed output contains the lambda values, log likelihoods, residual mean square errors, Akaike Information Criterion (AIC), and Schwarz's Bayesian Criterion (SBC).

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