2 papers
math.ST2026
On Statistical Inference for Rates of Change in Spatial Processes over Riemannian Manifolds
Didong Li, Aritra Halder, Sudipto Banerjee
Statistical inference for spatial processes from partially realized or scattered data has seen voluminous developments in diverse areas ranging from environmental sciences to busin…
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…