PySAL

 PySAL spreg, short for “spatial regression,” is a python package to estimate simultaneous autoregressive spatial regression models. These models are useful when modeling processes where observations interact with one another. The package is under active development by Luc Anselin and Pedro Amaral.

The package allows you to estimate spatial regression models and spatial regimes models (variants of spatial regression models that allow for structural instability in parameters, i.e. these models allow different coefficient values in distinct subsets of the data). It also includes seemingly-unrelated regressions (and their spatial generalizations) to allow for correlation in the residual terms between groups that use the same model. In spatial seemingly-unrelated regressions, the error terms across groups are allowed to exhibit a structured type of correlation: spatial correlation. In addition, spreg supports spatial panel models to evaluate correlation in both spatial and time dimensions, and diagnostics.

More about PySAL, managed by Serge Rey.

Anselin, L., & Rey, S. J. (2014). Modern Spatial Econometrics in Practice: A Guide to GeoDa, GeoDaSpace and PySAL.

Luc Anselin and Pedro Amaral manage PySAL’s spatial econometrics package spreg. Like GeoDa, spreg has also been downloaded 600,000 times: