Prediction of PM2.5 Concentration and Discovery of a PM2.5 Pathway in Seoul via Nonparanormal Graphical Models

Summary

We proposed the use of a nonparanormal graphical model to climate data to predict concentrations of PM2.5 and uncover a pathway of PM2.5 for SNU 2023 Spring Probabilistic Graphical Model Final Project. The nonparanormal graphical model exhibited strength in uncovering and representing hidden aspects of the climate data, shedding light on previously unidentified relationships.