COM Interface to R Environment

The R environment must be installed on the same computer with Statistica desktop or on the Statistica Server. The latest version of the R environment can be obtained from the CRAN website (http://cran.r-project.org).

To access the R environment, Statistica uses the COMadaptR library distributed under GNU Lesser Public License; this library has two components: one of them acts as an R COM Server; the other is used for callbacks from R to Statistica.

After R is installed, Statistica automatically detects and downloads the version of COMadaptR based on the R version installed on the machine. For example, for the version R 3.x, COMadaptR version 1 is detected and downloaded.

Tip: It is best practice to use R versions 3.6.1 and 4.2.2.

The next time you run Statistica, a dialog asks if R Integration should be enabled. Click Yes, and Statistica automatically installs the COMadaptR library and register one of the components with the Windows registry. Note that these steps might require administrative privileges – depending on your operating system version and settings, the system might ask you to confirm these actions, possibly requesting administrator credentials. In addition, access to the Internet is required since COMadaptR is downloaded from https://tran.tibco.com/statistica/.

Read the KB article, Manually enabling Statistica-R Integration for Statistica, for manual installation instructions for the COMadaptR support library.

Note: The COMadaptR library is independent from Statistica and remains on your computer until it is uninstalled manually.

The COMadaptR library provides a simple yet powerful COM (Component Object Model) interface to the R environment. This interface can be used directly by SVB programs in Statistica – an example of such a use case is included in the Statistica application, located in Examples\R\Dose Response folder (open Direct Interface To R via COM.stw and run the embedded SVB macro). But usage of such an interface directly by end users is very ineffective, sometimes unproductive, and usually inflexible. It may also significantly degrade the overall performance of interactions with R if performed incorrectly.

Therefore, the following architectural extensions have been added to the Statistica platform to provide a seamless and effective R Integration experience for end users. The example mentioned previously also demonstrates the significant reduction in the efforts required to implement the same analysis using the new built-in features in Statistica, simply open and run DoseResponse.r.