The MODEL Procedure

Model variables are declared by VAR, ENDOGENOUS, or EXOGENOUS statements, or by FIT and SOLVE statements. The model variables are the variables that the model is intended to explain or predict.

PROC MODEL enables you to use expressions on the left-hand side of the equal sign to define model equations. For example, a log-linear model for Y can be written as

   log( y ) = a + b * x;

Previously, only a variable name was allowed on the left-hand side of the equal sign.

The text on the left-hand side of the equation serves as the equation name used to identify the equation in printed output, in the OUT= data sets, and in FIT or SOLVE statements. To refer to equations specified by using left-hand side expressions (in the FIT statement, for example), place the left-hand side expression in quotes. For example, the following statements fit a log-linear model to the dependent variable Y:

   proc model data=in;
      log( y ) = a + b * x;
      fit "log(y)";
   run;

The estimation and simulation is performed by transforming the models into general form equations. No actual or predicted value is available for general form equations, so no or adjusted is computed.

An equation variable is one of several special variables used by PROC MODEL to control the evaluation of model equations. An equation variable name consists of one of the prefixes EQ, RESID, ERROR, PRED, or ACTUAL, followed by a period and the name of a model equation.

Equation variable names can appear in parts of the PROC MODEL printed output, and they can be used in the model program. For example, RESID-prefixed variables can be used in LAG functions to define equations with moving-average error terms. See the section Autoregressive Moving-Average Error Processes for details.

The meaning of these prefixes is detailed in the section Equation Translations.

Parameters are variables that have the same value for each observation. Parameters can be given values or can be estimated by fitting the model to data. During the SOLVE stage, parameters are treated as constants. If no estimation is performed, the SOLVE stage uses the initial value provided in the ESTDATA= data set, the MODEL= file, or in the PARAMETER statement, as the value of the parameter.

The PARAMETERS statement declares the parameters of the model. Parameters are not lagged, and they cannot be changed by the model program.

Control variables supply constant values to the model program that can be used to control the model in various ways. The CONTROL statement declares control variables and specifies their values. A control variable is like a parameter except that it has a fixed value and is not estimated from the data.

Control variables are not reinitialized before each pass through the data and can thus be used to retain values between passes. You can use control variables to vary the program logic. Control variables are not affected by lagging functions.

For example, if you have two versions of an equation for a variable Y, you could put both versions in the model and, by using a CONTROL statement to select one of them, produce two different solutions to explore the effect the choice of equation has on the model, as shown in the following statements:

   select (case);
      when (1) y =  ...first version of equation... ;
      when (2) y =  ...second version of equation... ;
   end;

   control case 1;
   solve / out=case1;
   run;

   control case 2;
   solve / out=case2;
   run;

The RANGE statement controls the range of observations in the input data set that is processed by PROC MODEL. The ID statement lists variables in the input data set that are used to identify observations in the printout and in the output data set. The BY statement can be used to make PROC MODEL perform a separate analysis for each BY group. The variable in the RANGE statement, the ID variables, and the BY variables are available for the model program to examine, but their values should not be changed by the program. The BY variables are not affected by lagging functions.

You can use several internal variables in the model program to communicate with the procedure. For example, if you want PROC MODEL to list the values of all the variables when more than 10 iterations are performed and the procedure is past the 20th observation, you can write

   if _obs_ > 20 then if _iter_ > 10 then _list_ = 1;

Internal variables are not affected by lagging functions, and they cannot be changed by the model program except as noted. The following internal variables are available. The variables are all numeric except where noted.

Variables not in any of the other classes are called program variables. Program variables are used to hold intermediate results of calculations. Program variables are reinitialized to missing values before each observation is processed. Program variables can be lagged. The RETAIN statement can be used to give program variables initial values and enable them to keep their values between observations.

PROC MODEL supports both numeric and character variables. Character variables are not involved in the model specification but can be used to label observations, to write debugging messages, or for documentation purposes. All variables are numeric unless they are the following.