Transfer the data to R. The following statements run the ExportMatrixToR subroutine in order to transfer data from a SAS/IML matrix into an R matrix. The names of the corresponding R vectors that contain the data are w and h.

/* send matrices to R */
run ExportMatrixToR(Weight, "w");
run ExportMatrixToR(Height, "h");

Call R functions to perform some analysis. The SUBMIT statement with the R option is used to send statements to R. Comments in R begin with a hash mark (#, also called a number sign or a pound sign).

submit / R;
   Model    <- lm(w ~ h, na.action="na.exclude")         # a
   ParamEst <- coef(Model)                               # b
   Pred     <- fitted(Model)
   Resid    <- residuals(Model)
endsubmit;

The R program consists of the following steps:

1. The lm function computes a linear model of w as a function of h. The na.action= option specifies how the model handles missing values (which in R are represented by NA). In particular, the na.exclude option specifies that the lm function should not omit observations with missing values from residual and predicted values. This option makes it easier to merge the R results with the original data when the data contain missing values.

2. Various information is retrieved from the linear model and placed into R vectors named ParamEst, Pred, and Resid.

Transfer the data from R. The ImportMatrixFromR subroutine transfers the ParamEst vector from R into a SAS/IML vector named pe. This vector is printed by the SAS/IML PRINT statement. The predicted values (Pred) and residual values (Resid) can be transferred similarly. The parameter estimates are used to compute the predicted values for a series of hypothetical heights, as shown in Figure 11.3.

run ImportMatrixFromR(pe, "ParamEst");
print pe[r={"Intercept" "Height"}];

ht = T( do(55, 70, 5) );
A = j(nrow(ht),1,1) || ht;
pred_wt = A * pe;
print ht pred_wt;