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What is PM2.5 Outlier Detection in Medellín about?

This document examines the impact of multivariate functional outlier identification and sample robustification on detecting critical PM2.5 air pollution episodes in Medellín, Colombia. It compares 18 depth-based outlier identification methods, applying the two most effective to a real dataset, and finds that while some methods perform better in specific scenarios, robustification did not yield clear benefits in accuracy for the real data. The study contributes to the field of functional data analysis in env

Author

solercruzelvermiguel

Language

EN