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This is a repository for the geographically-weighted regression submodule of the Python Spatial Analysis Library
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gwr Merge pull request pysal#27 from TaylorOshan/spat_var Mar 19, 2018
.travis.yml remove v 2.x tests from CI May 16, 2018
LICENSE initialize gwr submodule Nov 20, 2017
README.md minor updates to readme Nov 20, 2017
requirements.txt initialize gwr submodule Nov 20, 2017
requirements_dev.txt initialize gwr submodule Nov 20, 2017
setup.cfg prepare to upload to pypi Nov 20, 2017
setup.py bump version May 4, 2018

README.md

Geographically Weighted Regression

This module provides geographically weighted regression functionality. It is built upon the sparse generalized linear modeling (spglm) module.

Features

The gwr module currently features

  • gwr model estimation via iteratively weighted least squares for Gaussian, Poisson, and binomial probability models.
  • gwr bandwidth selection via golden section search
  • gwr-specific model diagnostics, including a multiple hypothesis testing correction
  • gwr-based spatial prediction

Future Work

  • Additional probability models (gamma, negative binomial)
  • Tests for spatial variability
  • Multi-scale gwr
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