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Arc_Mat, a Toolbox for Using ArcView Shape Files for Spatial Econometrics and Statistics

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Geographic Information Science (GIScience 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3234))

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Abstract

The ability to use statistical functionality for spatial modeling and analysis in conjunction with a mapping interface in the same environment has received a great deal of attention in the spatial analysis literature. We demonstrate the feasibility of extracting map polygon and database information from ESRI’s ArcView shape files for use in statistical software environments. Specifically, we show that information containing map polygons can be used in these environments to produce high quality mapping functionality. Improvements in recent computer graphics hardware and software allow basic plotting functionality that is part of statistical software environments to produce mapping functionality based on the high quality ArcView map polygons.

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References

  • Anselin, L., Syabri, I., Smirnov, O.: Visualizing Multivariate Spatial Correlation with Dynamically Linked Windows. In: Anselin, L., Rey, S. (eds.) Proc. CSISS Workshop on New Tools for Spatial Data Analysis, Santa Barbara, CA, Center for Spatially Integrated Social Science (2002) CD-ROM (pdf file, 20 pp.)

    Google Scholar 

  • Barry, R., Pace, R.K.: A Monte Carlo Estimator of the Log Determinant of Large Sparse Matrices. Linear Algebra and its Applications 289, 41–54 (1999)

    Article  MATH  MathSciNet  Google Scholar 

  • Bivand, R.S.: Spatial econometrics functions in R: Classes and methods. Journal of Geographical Systems 4, 405–421 (2002)

    Article  Google Scholar 

  • Brunsdon, C., Fotheringham, A.S., Charlton, M.E.: Geographically weighted regression: A method for exploring spatial non-stationarity. Geographical Analysis 28, 281–298 (1996)

    Article  Google Scholar 

  • Geweke, J.: Bayesian Treatment of the Independent Student t Linear Model. Journal of Applied Econometrics 8, 19–40 (1993)

    Article  Google Scholar 

  • Heba, I., E. Malin, and C. Thomas-Agnan: Exploratory spatial data analysis with GEOXP. European Regional Science Association conference papers

    Google Scholar 

  • LeSage, J.P.: Bayesian Estimation of Spatial Autoregressive Models. International Regional Science Review 20, 113–129 (1997)

    Article  Google Scholar 

  • LeSage, J.P.: The Theory and Practice of Spatial Econometrics (1999) pdf file, 296 pp. available at http://www.spatial-econometrics.com

  • LeSage, J.P.: A Family of Geographically Weighted Regression Models. In: Anselin, L., Florax, J.G.M., Rey, S.J. (eds.) Advances in Spatial Econometrics, Springer, Heidelberg (to appear)

    Google Scholar 

  • Pace, R. K.: Spatial Statistics Toolbox 2.0. (2002) pdf file, 36 pp. available at www.spatial-statistics.com .

  • Pace, R.K., Barry, R.: Quick Computation of Regressions with a Spatially Autoregressive Dependent Variable. Geographical Analysis 29, 232–247 (1997)

    Article  Google Scholar 

  • Pace, R.K., LeSage, J.P.: Spatial Autoregressive Local Estimation. In: Mur, J., Zoller, H., Getis, A. (eds.) Recent Advances in Spatial Econometrics, pp. 31–51. Palgrave Publishers (2004)

    Google Scholar 

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© 2004 Springer-Verlag Berlin Heidelberg

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LeSage, J.P., Pace, R.K. (2004). Arc_Mat, a Toolbox for Using ArcView Shape Files for Spatial Econometrics and Statistics. In: Egenhofer, M.J., Freksa, C., Miller, H.J. (eds) Geographic Information Science. GIScience 2004. Lecture Notes in Computer Science, vol 3234. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30231-5_12

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  • DOI: https://doi.org/10.1007/978-3-540-30231-5_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23558-3

  • Online ISBN: 978-3-540-30231-5

  • eBook Packages: Springer Book Archive

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