Getting Started with C++ for Faster Forecasting in R

A hands-on WOMBAT 2026 tutorial on speeding up R with C++, from RStudio setup to forecasting applications, with Tomasz Wozniak.
Published

November 30, 2026

November 30, 09:00 AM

Getting Started with C++ for Faster Forecasting in R

Code written in C++ runs significantly faster than code written in R, which provides the basis for many leading R packages. This design enables users to leverage the best of both worlds: the computational speed delivered by algorithms written in C++ and the convenience of data analysis in R. Fortunately, recent developments have simplified programming in C++ for R applications by automating many processes.

In this session, Tomasz will guide attendees through the basics of this approach, working in RStudio, ensuring object compatibility, using basic algorithmic structures, functional programming, linear algebra, and extending R packages with C++ code. A sequence of hands-on exercises with applications to forecasting supports all this.

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Tomasz Woźniak

Tomasz Woźniak

Tomasz Woźniak is a Bayesian econometrician developing new econometric methods for applied macroeconomic research. He has been a specialised R user for eighteen years and has recently joined The R Journal as an Associate Editor. He is the author of several R packages, available at https://bsvars.org/, that combine blazingly fast algorithms written in C++ with the convenience of data analysis in R. He works as a senior lecturer at the University of Melbourne, where he has an extensive research, teaching, and engagement portfolio.