Arc_Mat: a Matlab-based spatial data analysis toolbox. This article presents an overview of Arc_Mat, a Matlab-based spatial data analysis software package whose source code has been placed in the public domain. An earlier version of the Arc_Mat toolbox was developed to extract map polygon and database information from ESRI shapefiles and provide high quality mapping in the Matlab software environment. We discuss revisions to the toolbox that: utilize enhanced computing and graphing capabilities of more recent versions of Matlab, restructure the toolbox with object-oriented programming features, and provide more comprehensive functions for spatial data analysis. The Arc_Mat toolbox functionality includes basic choropleth mapping; exploratory spatial data analysis that provides exploratory views of spatial data through various graphs, for example, histogram, Moran scatterplot, three-dimensional scatterplot, density distribution plot, and parallel coordinate plots; and more formal spatial data modeling that draws on the extensive Spatial Econometrics Toolbox functions. A brief review of the design aspects of the revised Arc_Mat is described, and we provide some illustrative examples that highlight representative uses of the toolbox. Finally, we discuss programming with and customizing the Arc_Mat toolbox functionalities.

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  9. Glass, Anthony J.; Kenjegalieva, Karligash; Weyman-Jones, Thomas: The effect of monetary policy on bank competition using the Boone index (2020)
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  12. Hou, Zhezhi; Jin, Man; Kumbhakar, Subal C.: Productivity spillovers and human capital: a semiparametric varying coefficient approach (2020)
  13. Huang, Danyang; Wang, Feifei; Zhu, Xuening; Wang, Hansheng: Two-mode network autoregressive model for large-scale networks (2020)
  14. Jeong, Hanbat; Lee, Lung-fei: Spatial dynamic models with intertemporal optimization: specification and estimation (2020)
  15. Kutlu, Levent; Tran, Kien C.; Tsionas, Mike G.: A spatial stochastic frontier model with endogenous frontier and environmental variables (2020)
  16. Lebacher, Michael; Thurner, Paul W.; Kauermann, Göran: Exploring dependence structures in the international arms trade network: a network autocorrelation approach (2020)
  17. Ma, Yingying; Lan, Wei; Zhou, Fanying; Wang, Hansheng: Approximate least squares estimation for spatial autoregressive models with covariates (2020)
  18. Mínguez, Román; Basile, Roberto; Durbán, María: An alternative semiparametric model for spatial panel data (2020)
  19. Murakami, Daisuke; Griffith, Daniel A.: A memory-free spatial additive mixed modeling for big spatial data (2020)
  20. Skevas, Ioannis: Inference in the spatial autoregressive efficiency model with an application to Dutch dairy farms (2020)

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