Geostatistical space–time mapping of house prices using Bayesian maximum entropy

References

• Angulo, J., et al., 2013. Spatiotemporal infectious disease modeling: a BME-SIR approach. PLoS ONE, 8 (9), e72168. doi:10.1371/journal.pone.0072168
   PubMed Web of Science ®Google Scholar
• Banerjee, S., Carlin, B.P., and Gelfand, A.E., 2004. Hierarchical modeling and analysis for spatial data. Boca Raton, FL: Chapman & Hall/CRC.
   Google Scholar
• Chica-Olmo, J., 2007. Prediction of housing location price by a multivariate spatial method: Cokriging. Journal of Real Estate Research, 29 (1), 91–114.
   Web of Science ®Google Scholar
• Chilès, J.P. and Delfiner, P., 1999. Geostatistics-modeling spatial uncertainty. New York, NY: John Wiley & Sons.
   Google Scholar
• Cho, Y., Hwang, S., and Lee, Y., 2014. The dynamics of appraisal smoothing. Real Estate Economics, 42 (2), 497–529. doi:10.1111/reec.2014.42.issue-2
   Web of Science ®Google Scholar
• Christakos, G., 1991. On certain classes of spatiotemporal random fields with application to space-time data processing. IEEE-Trans on Systems, Man, and Cybernetics, 21 (4), 861–875. doi:10.1109/21.108303
   Web of Science ®Google Scholar
• Christakos, G., 1992. Random field models in earth sciences. San Diego, CA: Academic Press.
   Google Scholar
• Christakos, G., 2000. Modern spatiotemporal geostatistics. New York, NY: Oxford University Press.
   Google Scholar
• Christakos, G., 2010. Integrative problem-solving in a time of decadence. New York, NY: Springer-Verlag.
   Google Scholar
• Christakos, G., 2014. Stochastic medical reasoning and environmental health exposure. London: Imperial College Press.
   Google Scholar
• Christakos, G., Bogaert, M.P., and Serre, M.L., 2002. Temporal GIS. With CD-ROM. New York, NY: Springer-Verlag.
   Google Scholar
• Christakos, G., Hristopulos, D.T., and Bogaert, P., 2000. On the physical geometry concept at the basis of space/time geostatistical hydrology. Advances in Water Resources, 23 (8), 799–810. doi:10.1016/S0309-1708(00)00020-8
   Web of Science ®Google Scholar
• Cressie, N. and Wickle, C.K., 2011. Statistics for spatio-temporal data. Hoboken, NJ: John Wiley & Sons.
   Google Scholar
• Dubin, R.A., 1998. Predicting house prices using multiple listing data. The Journal of Real Estate Finance and Economics, 17 (1), 35–59. doi:10.1023/A:1007751112669
   Web of Science ®Google Scholar
• Gelfand, A.E., et al., 2004. The dynamics of location in home price. Journal of Real Estate Finance and Economics, 29 (2), 149–166. doi:10.1023/B:REAL.0000035308.15346.0a
   Web of Science ®Google Scholar
• Goodman, A., 1977. A comparison of block group and census tract data in a hedonic housing price model. Land Economics, 53, 483–487. doi:10.2307/3145991
   Web of Science ®Google Scholar
• Goovaerts, P., 1997. Geostatistics for natural resources evaluation. New York, NY: Oxford University Press.
   Google Scholar
• Helbich, M., 2015. Do suburban areas impact house prices? Environment and Planning B: Planning and Design, 42, 431–449. doi:10.1068/b120023p
   Web of Science ®Google Scholar
• Journel, A.G., 1989. Fundamentals of geostatistics in five lessons. Washington, DC: American Geophysical Union.
   Google Scholar
• Kolovos, A., et al., 2002. Computational Bayesian maximum entropy solution of a stochastic advection-reaction equation in the light of site-specific information. Water Resource Research, 38 (12), 1318–1334. doi:10.1029/2001WR000743
   Web of Science ®Google Scholar
• Kolovos, A., et al., 2004. On certain classes of non-separable spatiotemporal covariance models. Advances in Water Resources, 27, 815–830. doi:10.1016/j.advwatres.2004.04.002
   Web of Science ®Google Scholar
• Kolovos, A., et al., 2010. Multi-perspective analysis and spatiotemporal mapping of air pollution monitoring data. Environmental Science and Technology, 44 (17), 6738–6744. doi:10.1021/es1013328
   PubMed Web of Science ®Google Scholar
• Kolovos, A., et al., 2013. Model-driven development of covariances for spatiotemporal environmental health assessment. Environmental Monitoring and Assessment, 185 (1), 815–831. doi:10.1007/s10661-012-2593-1
   PubMed Web of Science ®Google Scholar
• Kuntz, M. and Helbich, M., 2014. Geostatistical mapping of real estate prices: an empirical comparison of kriging and cokriging. International Journal of Geographical Information Science, 28 (9), 1904–1921. doi:10.1080/13658816.2014.906041
   Web of Science ®Google Scholar
• LeSage, J.P. and Pace, R.K., 2009. Introduction to spatial econometrics. Boca Raton, FL: Chapman and Hall/CRC.
   Google Scholar
• Montero, J.M. and Larraz, B., 2011. Interpolation methods for geographical data: housing and commercial establishment markets. Journal of Real Estate Research, 33 (2), 233–244.
   Web of Science ®Google Scholar
• Nappi-Choulet, I. and Maury, T.-P., 2011. A spatial and temporal autoregressive local estimation for the Paris housing market. Journal of Regional Science, 51 (4), 732–750. doi:10.1111/jors.2011.51.issue-4
   Web of Science ®Google Scholar
• Páez, A., Long, F., and Farber, S., 2008. Moving window approaches for hedonic price estimation: an empirical comparison of modelling techniques. Urban Studies, 45 (8), 1565–1581. doi:10.1177/0042098008091491
   Web of Science ®Google Scholar
• Pinkse, J. and Slade, M.E., 2010. The future of spatial econometrics. Journal of Regional Science, 50 (1), 103–117. doi:10.1111/jors.2010.50.issue-1
   Web of Science ®Google Scholar
• Plummer, E., 2015. The effects of property tax protests on the assessment uniformity of residential properties. Real Estate Economics, 42 (4), 900–937. doi:10.1111/1540-6229.12080
   Web of Science ®Google Scholar
• Quan, D.C. and Quigley, J., 1991. Price formation and the appraisal function in real estate markets. The Journal of Real Estate Finance and Economics, 4, 127–146. doi:10.1007/BF00173120
   Web of Science ®Google Scholar
• Savelyeva, E., et al., 2010. Modeling spatial uncertainty for locally uncertain data. In: P.M. Atkinson and C.D. Lloyd, et al., eds. geoENV VII–geostatistics for environmental applications: quantitative geology and geostatistics. Springer: The Netherlands, 295–306.
   Google Scholar
• Yoo, E.-H. and Kyriakidis, P.C., 2009. Area-to point kriging in spatial hedonic pricing models. Journal of Geographical Systems, 11, 381–406. doi:10.1007/s10109-009-0090-z
   Web of Science ®Google Scholar
• Yu, H.-L., et al., 2007. Interactive spatiotemporal modelling of health systems: the SEKS-GUI framework. Stochastic Environmental Research and Risk Assessment, 21 (5), 555–572. doi:10.1007/s00477-007-0135-0
   Web of Science ®Google Scholar
• Yu, H.-L., Ku, S.-J., and Kolovos, A., 2015. A GIS-based tool for spatiotemporal modeling under a knowledge synthesis framework. Stoch Environ Res Risk Assess. doi:10.1007/s00477-015-1078-5.
   PubMed Web of Science ®Google Scholar
• Zagouras, A., Kolovos, A., and Coimbra, C.F.M., 2015. Objective framework for optimal distribution of solar irradiance monitoring networks. Renewable Energy, 80, 153–165. doi:10.1016/j.renene.2015.01.046
   Web of Science ®Google Scholar