A Practical Introduction to R torch For Statisticians and Psychometricians
Yinuo Cheng, Weicong Lyu, Chun Wang · Journal of Educational and Behavioral Statistics · 2026
The growing scale and complexity of statistical and psychometric analyses call for tools that are efficient, flexible, and accessible within the R ecosystem. This article presents R torch , a high-performance tensor computing framework with automatic differentiation that brings core PyTorch capabilities to R. We offer a hands-on tutorial that demonstrates vectorized computation, automatic differentiation, and Graphics Processing Unit (GPU) acceleration for common tasks, with case studies showing concise code and substantial gains in speed and scalability over base R. Practical guidance for reliable, readable, and reproducible implementation is included. This tutorial emphasizes conceptual clarity and reproducibility, positioning R torch as a bridge between traditional statistical workflows and modern large-scale computational methods.