anomalize

Seamlessly works with dplyr and ggplot2 in a pipe-friendly workflow, as shown in the quick start example using %>% for data manipulation and visualization.

Uses methods like STL to break time series into seasonal, trend, and remainder components, enabling focused anomaly detection on the remainder.

Includes plot_anomalies() and plot_anomaly_decomposition() for clear visual insights, demonstrated with the tidyverse_cran_downloads dataset.

The clean_anomalies() function repairs outliers, which the README notes can reduce forecast error by up to 32% in examples.