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PySAL: A Python Library of Spatial Analytical Methods

  • Rey, Sergio J.

    (San Diego State U)

  • Anselin, Luc

    (U IL)

PySAL is an open source library for spatial analysis written in the object-oriented language Python. It is built upon shared functionality in two exploratory spatial data analysis packages--GeoDA and STARS--and is intended to leverage the shared development of these components. This paper presents an overview of the motivation behind and the design of PySAL, as well as suggestions for how the library can be used with other software projects. Empirical illustrations of several key components in a variety of spatial analytical problems are given, and plans for future development of PySAL are discussed.

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Article provided by Southern Regional Science Association in its journal Review of Regional Studies.

Volume (Year): 37 (2007)
Issue (Month): 1 ()
Pages: 5-27

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Handle: RePEc:rre:publsh:v:37:y:2007:i:1:p:5-27
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  1. Harry H. Kelejian & Ingmar R. Prucha, 1997. "A Generalized Spatial Two Stage Least Squares Procedure for Estimating a Spatial Autoregressive Model with Autoregressive Disturbances," Electronic Working Papers 97-002, University of Maryland, Department of Economics, revised Aug 1997.
  2. Luc Anselin & Yong Wook Kim & Ibnu Syabri, 2004. "Web-based analytical tools for the exploration of spatial data," Journal of Geographical Systems, Springer, vol. 6(2), pages 197-218, 06.
  3. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-38, May.
  4. Luc Anselin & Harry H. Kelejian, 1997. "Testing for Spatial Error Autocorrelation in the Presence of Endogenous Regressors," International Regional Science Review, SAGE Publishing, vol. 20(1-2), pages 153-182, April.
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