152 citations · 232 across the 10 of their papers we have counts for
11 papers
Prediction of Tropical Pacific Rain Rates with Over-parameterized Neural Networks
Hojun You, Jiayi Wang, Raymond K. W. Wong +3
The prediction of tropical rain rates from atmospheric profiles poses significant challenges, mainly due to the heavy-tailed distribution exhibited by tropical rainfall. This study…
3D Bivariate Spatial Modelling of Argo Ocean Temperature and Salinity
Mary Lai Salvana, Jian Cao, Mikyoung Jun
Variables contained within the global oceans can detect and reveal the effects of the warming climate as the oceans absorb huge amounts of solar energy. Hence, information regardin…
Flexible Spatio-Temporal Hawkes Process Models for Earthquake Occurrences
Junhyeon Kwon, Yingcai Zheng, Mikyoung Jun
Hawkes process is one of the most commonly used models for investigating the self-exciting nature of earthquake occurrences. However, seismicity patterns have complicated character…
On minimum contrast method for multivariate spatial point processes
Lin Zhu, Junho Yang, Mikyoung Jun +1
Compared to widely used likelihood-based approaches, the minimum contrast (MC) method offers a computationally efficient method for estimation and inference of spatial point proces…
Flexible multivariate spatio-temporal Hawkes process models of terrorism
Mikyoung Jun, Scott Cook
We develop flexible multivariate spatio-temporal Hawkes process models to analyze patterns of terrorism. Previous applications of point process methods to political violence data m…
The promise and perils of point process models of political events
Lin Zhu, Scott J. Cook, Mikyoung Jun
Event data are increasingly common in applied political science research. While these data are inherently locational, political scientists predominately analyze aggregate summaries…