Here are some images and tools that serve a similar purpose to the Rocker images. Please refer to the links for more information.
1 Docker images for R
1.1 Jupyter Docker Stacks
The stack of Docker images by Project Jupyter, based on Ubuntu, install packages from conda-forge, and configured to run Jupyter.
It includes several images with the R package already installed, such as jupyter/r-notebook and jupyter/datascience-notebook, so you can immediately run R on Jupyter.
1.2 b-data/jupyterlab-r-docker-stack
Multi-arch (linux/amd64, linux/arm64/v8) docker images based on Debian including code-server (vscode in the browser).
Images considered stable for R versions ≥ 4.2.0.
1.3 r-hub/r-minimal
Very small size image with R installed on alpine.
1.4 RStudio R Docker Images
Images of RStudio built and installed R binaries.
1.5 Docker containers for Bioconductor
Bioconductor docker images with system dependencies to install all packages. Based on rocker/rstudio.
1.6 rhub-linux-builders
Docker configuration for the Linux builders of the R-hub package builder. These images are useful for you to run to debug your R package.
1.7 runiverse/base
A docker image for building R source packages and documentation, used in the R-universe build tool.
2 Other tools
2.1 Mamba
A package manager to install various packages from conda-forge and others.
If you use Mamba on Linux for R, it may be easier to install packages, see also the Extending images page.
2.2 rig
An R Installation Manager (Previously known as rim).
With rig, you can easily install and switch between specific versions of R.
2.3 rsi
Intended for system administrators who want to perform a source-installation of R.
It is meant for installing official releases of R source code on Debian-based Linux distributions, e.g. Ubuntu, using a docker container.