Supplementary document of 'Mo-LOO-KDE for Anomaly Detection in Satellite Telemetry'

This is the supplementary material for the paper: Morphological Leave-One-Out Kernel Density Estimates for Anomaly Detection in Satellite Telemetry by Mina Bikhit, Sevvandi Kandanaarachchi, Krzysztof Kotowski, Jakub Nalepa, Bogdan Ruszczak mo_loo_kde.zip - The containerized configuration that enables the execution of a streamlined and reproducible experiment. The package with a configured environment capable of integrating Python and R programming languages. Given that the backbone anomaly detector LOO-KDE is implemented in R, while the rest of our workflow relied on Python, we utilized Docker to bridge between the two environments. Mo-LOO-KDE_Supplement.pdf - The supplementary material for the main paper: Morphological Leave-One-Out Kernel Density Estimates for Anomaly Detection in Satellite Telemetry. We provide several additional tables, figures, and a detailed algorithm within this document.