The `torch`

package for R (found here) is CRAN-installable and provides automatic differentiation in R, as long as you’re willing to rewrite your code using Torch functions.

The current docs for the `torch`

package are great, but assume you’re interested in machine learning. But gradients are useful for ordinary statistics, too! In the notebook below I fit a simple Poisson regression model using `optim`

by implementing the log likelihod and derivatives in torch. Though not really competitive with (the highly optimized) `lme4::glm`

on this toy example, the my point is more how easily you can roll your own MLE in R using `torch`

.

The notebook itself can be downloaded here, and an markdown version follows.

{% include_relative html/2022-04-01_poisson_regression_torch_for_r.md %}