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stat.ME2025
The Nearest-Neighbor Derivative Process: Modeling Spatial Rates of Change in Massive Datasets
Jiawen Chen, Aritra Halder, Yun Li +2
Gaussian processes (GPs) are instrumental in modeling spatial processes, offering precise interpolation and prediction capabilities across fields such as environmental science and…
stat.ME2024
Bayesian Spatiotemporal Wombling
Aritra Halder, Didong Li, Sudipto Banerjee
Stochastic process models for spatiotemporal data underlying random fields find substantial utility in a range of scientific disciplines. Subsequent to predictive inference on the…