spatial-statistics
Installation
SKILL.md
Spatial Statistics
Purpose: answer "is it clustered, where, and why" with defensible inference. The core discipline: spatial data violates independence assumptions, so standard statistics silently overstate significance — every analysis here starts with weights design and ends with residual diagnostics.
Spatial weights (W) — the analysis IS the weights
Every result downstream depends on W; choose it for substantive reasons and run a sensitivity check with one alternative:
| Weights | Use when |
|---|---|
| Queen/Rook contiguity | Irregular polygons (admin units, parcels) |
| K-nearest neighbors | Points; islands present (contiguity leaves them unconnected) |
| Distance band | Physical process with known range |
| Kernel (distance-decayed) | Smooth influence, GWR-style local models |