Preprint
Aug 2026
A Deep Learning Model for Spatially Clustered Data via Differentiable Cluster Assignment
Simulations show that joint estimation is useful when regression surfaces change abruptly across spatial boundaries, including settings with nonlinear effects, unequal region sizes, preferential sampling, and spatially correlated errors.
Ke-Xuan Li, Wei-Dong Ma
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