You do not need to do anything special to call an R package. Provided that an R package is installed, you can call `library(`*package*** )** from inside a SUBMIT block to load the package. You can then call the functions in the package.

Similarly, you do not need to do anything special to call R graphics. The graph appears in the standard R graphics window.

The example in this section calls an R package and creates a graph in R.

In Chapter 6, Adding Curves to Graphs, you called the KDE procedure to compute a kernel density estimate for the min_pressure variable in the Hurricanes data set. The following program reproduces that analysis by calling functions in the KernSmooth package and creating a histogram in R:

declare DataObject dobj; dobj = DataObject.CreateFromFile("Hurricanes"); dobj.GetVarData("min_pressure", p); run ExportMatrixToR( p, "Pressure" ); submit / R; library(KernSmooth) idx <-which(!is.na(Pressure)) # must exclude missing values (NA) p <- Pressure[idx] # from KernSmooth functions h = dpik(p) # Sheather-Jones plug-in bandwidth est <- bkde(p, bandwidth=h) # est has 2 columns hist(p, breaks="Scott", freq=FALSE, col="lightyellow") # histogram lines(est) # kde overlay endsubmit;

The program creates an R matrix ** Pressure** from the data in the min_pressure variable. Because the functions in the KernSmooth package do not handle missing values, the nonmissing values in

The ** hist** function creates a histogram of the data in the

The R graphics window contains the histogram, which is shown in Figure 11.5. You can compare the histogram and density estimate created by R with the IMLPlus graph shown in Figure 6.4.