An assessment of coefficient accuracy in linear regression models with spatially varying coefficients
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Bibliographic InfoArticle provided by Springer in its journal Journal of Geographical Systems.
Volume (Year): 9 (2007)
Issue (Month): 2 (June)
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Web page: http://www.springerlink.com/link.asp?id=103079
Bayesian regression; Geographically weighted regression; MCMC; Simulation study; Spatial statistics; Collinearity;
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- Gelfand A.E. & Kim H-J. & Sirmans C.F. & Banerjee S., 2003. "Spatial Modeling With Spatially Varying Coefficient Processes," Journal of the American Statistical Association, American Statistical Association, vol. 98, pages 387-396, January.
- Alan Gelfand & Alexandra Schmidt & Sudipto Banerjee & C. Sirmans, 2004. "Nonstationary multivariate process modeling through spatially varying coregionalization," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer, vol. 13(2), pages 263-312, December.
- David Wheeler & Lance Waller, 2009. "Comparing spatially varying coefficient models: a case study examining violent crime rates and their relationships to alcohol outlets and illegal drug arrests," Journal of Geographical Systems, Springer, vol. 11(1), pages 1-22, March.
- Redfearn, Christian L., 2009. "How informative are average effects? Hedonic regression and amenity capitalization in complex urban housing markets," Regional Science and Urban Economics, Elsevier, vol. 39(3), pages 297-306, May.
- Paolo Postiglione & M. Andreano & Roberto Benedetti, 2013. "Using Constrained Optimization for the Identification of Convergence Clubs," Computational Economics, Society for Computational Economics, vol. 42(2), pages 151-174, August.
- Cem Ertur & Julie Le Gallo, 2008. "Regional Growth and Convergence: Heterogenous reaction versus interaction in spatial econometric approaches," Working Papers hal-00463274, HAL.
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