# TODO: oxigdal-analytics
## High Priority
- [ ] Implement Universal Kriging with external drift variables
- [ ] Add co-kriging for multivariate spatial interpolation
- [ ] Implement OPTICS clustering as DBSCAN alternative
- [ ] Add Geographically Weighted Regression (GWR)
- [ ] Implement Local Moran's I scatterplot classification (HH/HL/LH/LL)
- [ ] Add parallel execution for zonal statistics on large rasters
## Medium Priority
- [ ] Implement kernel density estimation (KDE) for point patterns
- [ ] Add Ripley's K/L function for spatial point pattern analysis
- [ ] Implement semivariogram cloud and model fitting (spherical, exponential, Gaussian)
- [ ] Add spatial regression models (SAR, SEM, SDM)
- [ ] Implement Random Forest spatial classification
- [ ] Add cross-validation framework for interpolation methods
- [ ] Implement Empirical Bayesian Kriging
- [ ] Add Multi-Resolution Index of Valley Bottom Flatness (MRVBF)
- [ ] Implement ISODATA unsupervised classification
## Low Priority / Future
- [ ] Add space-time kriging for spatiotemporal interpolation
- [ ] Implement agent-based spatial simulation framework
- [ ] Add network-constrained spatial analysis (shortest path, service area)
- [ ] Implement fuzzy overlay analysis
- [ ] Add spatial sampling strategies (random, stratified, systematic, Latin hypercube)
- [ ] Implement multi-criteria decision analysis (MCDA/AHP)