Embedding R in Windows applications, and executing R remotely
Embedding R in Windows applications, and executing R remotely
Embedding R in Windows applications, and executing R remotely
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Us<strong>in</strong>g R <strong>in</strong> other Applications<br />
Various practical ways to <strong>in</strong>tegrate an own<br />
software <strong>and</strong> R<br />
Simon Urbanek<br />
University of Augsbung<br />
R provides a flexible, computational framework for statistical data analysis.<br />
Due to its modularity the spectrum of available functions is be<strong>in</strong>g cont<strong>in</strong>uously<br />
extended. This functionality is typically used from the R comm<strong>and</strong> shell where<br />
the user performs an analysis. On the other h<strong>and</strong> many <strong>applications</strong> provide a<br />
different <strong>in</strong>terface to the user, ma<strong>in</strong>ly to reach different target groups of users,<br />
but are <strong>in</strong> need of the functionality R provides. Instead of re-implement<strong>in</strong>g such<br />
functions, it is more efficient to <strong>in</strong>tegrate R <strong>in</strong> the application or vice versa. In<br />
this talk we present the various methods of <strong>in</strong>tegration: l<strong>in</strong>k<strong>in</strong>g own code to R,<br />
l<strong>in</strong>k<strong>in</strong>g R <strong>in</strong>to an own application, us<strong>in</strong>g <strong>in</strong>ter-process communication or other<br />
packages offer<strong>in</strong>g specific <strong>in</strong>terfaces to R. The focus is placed on practical examples<br />
us<strong>in</strong>g the various techniques, as well as explanation of the implementation<br />
<strong>and</strong> limitations of each approach. In particular the methods are illustrated on<br />
a web server application us<strong>in</strong>g R <strong>and</strong> graphical <strong>in</strong>terfaces to R.<br />
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