`RESTRICT`

restriction1 < , restriction2 …> ;

The RESTRICT statement imposes linear restrictions on the parameter estimates. You can specify any number of RESTRICT statements.

Each *restriction* is written as an expression, followed by an equality operator (=) or an inequality operator (<, >, <=, >=), followed by a
second expression:

```
expression operator expression ;
```

The *operator* can be =, <, >, <= , or >=.

Restriction expressions can be composed of parameters; multiplication (), summation (), and substraction () operators; and constants. Parameters named in restriction expressions must be among the parameters estimated by the model. Parameters associated with a regressor variable are referred to by the name of the corresponding regressor variable. The restriction expressions must be a linear function of the parameters.

Lagrange multipliers are reported for all the active linear constraints. In the displayed output, the Lagrange multiplier
estimates are identified with the names `Restrict1`

, `Restrict2`

, and so on. The probability of the Lagrange multipliers is computed using a beta distribution (LaMotte 1994).

The following are examples of using the RESTRICT statement:

proc mdc data=one; model y = x1-x10 / type=clogit choice=(mode 1 2 3); id pid; restrict x1*2 <= x2 + x3, ; run;

proc mdc data=newdata; model decision = ttime / type=mprobit nchoice=3 unitvariance=(1 2) covest=hess; id pid; restrict RHO_31 = 0, STD_3<=1; run;