Trends

The current trends in R packages highlight a focus on **data analysis, machine learning, and visualization**. Packages like **`templateICAr`** and **`tseriesTARMA`** cater to the growing need for analyzing complex time series data, particularly in fields like neuroscience and finance. **`mlflow`** provides an interface to the popular machine learning platform, reflecting the increasing adoption of ML in R. The emphasis on visualization is evident in packages like **`ggtangle`**, which extends the powerful **`ggplot2`** framework for network visualization, and **`shinytest2`**, which facilitates automated testing of Shiny applications. Furthermore, there's a strong focus on **package development and infrastructure**. **`pkgKitten`** simplifies package creation for beginners, while **`S7`** offers a modern object-oriented programming system as a potential successor to S3 and S4. Finally, the trend towards **specialized tools** is evident in packages like **`fragility`**, which provides functions for assessing the robustness of clinical results, and **`zctaCrosswalk`**, which facilitates working with US Census data.