References
- Adair, A., Downie, M., & McGreal, S. (1996). European valuation practice. London: E&FN Spon.
- Andrienko, G., Andrienko, N., Bak, P., Keim, D., & Wrobel, S. (2013). Visual analytics of movement. Berlin: Springer.
- Andrienko, N., & Andrienko, G. (2006). Exploratory analysis of spatial and temporal data: A systematic approach. Berlin: Springer.
- Andrienko, N., & Andrienko, G. (2011). Spatial generalization and aggregation of massive movement data. IEEE Transactions on Visualization and Computer Graphics, 17(2), 205–219. doi: 10.1109/TVCG.2010.44
- Andrienko, N., & Andrienko, G. (2013). A visual analytics framework for spatio-temporal analysis and modelling. Data Mining and Knowledge Discovery, 27(1), 55–83.
- Anselin, L. (1998). GIS research infrastructure for spatial analysis of real estate markets. Journal of Housing Research, 9(1), 113–133.
- Brunsdon, C., Fotheringham, A. S., & Charlton, M. E. (1996). Geographically weighted regression: A method for exploring spatial nonstationarity. Geographical Analysis, 28(4), 281–298. doi: 10.1111/j.1538-4632.1996.tb00936.x
- Davies, H., Edwards, D., Punter, J., & Hooper, A. (1989). Planning control in Western Europe. London: HMSO.
- Demšar, U., Fotheringham, A. S., & Charlton, M. (2008). Exploring the spatio-temporal dynamics of geographical processes with geographically weighted regression and geovisual analytics. Information Visualization, 7, 181–197. doi: 10.1057/palgrave.ivs.9500187
- Garg, S., Ramakrishnan, I. V., & Mueller, K. A. (2010). Visual analytics approach to model learning. Proceedings of IEEE symposium on visual analytics science and technology, VAST’10, Salt Lake City, Utah, USA, pp. 67–74.
- Guo, Z., Ward, M. O., & Rundensteiner, E. A. (2009). Model space visualization for multivariate linear trend discovery. Proceedings of IEEE symposium on visual analytics science and technology, VAST’09, Atlantic City, NJ, USA, pp. 75–82.
- Hui, S. K., Cheung, A., & Pang, J. A. (2010). Hierarchical Bayesian approach for residential property valuation. International Real Estate Review, 13(1), 1–29.
- Kauko, T., & d’Amato, M. (2008). Mass appraisal methods: An international perspective for property valuers. Chichester, UK: Wiley-Blackwell.
- Maciejewski, R., Livengood, P., Rudolph, S., Collins, T. F., Ebert, D. S., Brigantic, R. T., … Sanders, S. W. (2011). A pandemic influenza modeling and visualization tool. Journal of Visual Languages and Computing, 22, 268–278. doi: 10.1016/j.jvlc.2011.04.002
- Matković, K., Gračanin, D., Jelović, M., Ammer, A., Lež, A., & Hauser, H. (2010). Interactive visual analysis of multiple simulation runs using the simulation model view: Understanding and tuning of an electronic unit injector. IEEE Transactions on Visualization and Computer Graphics, 16(6), 1449–1457. doi: 10.1109/TVCG.2010.171
- Migut, M., & Worring, M. (2010). Visual exploration of classification models for risk assessment. Proceedings of IEEE symposium on visual analytics science and technology, VAST’10, Salt Lake City, Utah, USA, pp. 11–18.
- Muhlbacher, T., & Piringer, H. (2013). A partition-based framework for building and validating regression models. IEEE Transactions on Visualization and Computer Graphics, 19(12), 1962–1971. doi: 10.1109/TVCG.2013.125
- Musgrave, R., & Musgrave, P. (2009). Public finance: Theory and practice. Business Atlas. New York: McGraw-Hill.
- Qian, Y., & Weingast, B. (1996). China’s transition to markets: Market-preserving federalism, Chinese style. The Journal of Policy Reform, 1, 149–185. doi: 10.1080/13841289608523361
- Rinzivillo, S., Pedreschi, D., Nanni, M., Giannotti, F., Andrienko, N., & Andrienko, G. (2008). Visually driven analysis of movement data by progressive clustering. Information Visualization, 7(3/4), 225–239. doi: 10.1057/palgrave.ivs.9500183
- Ryumkin, A. (2006). Reforming the management framework of urban land use. Studies on Russian Economic Development, 17(2), 83–90. doi: 10.1134/S1075700706010096
- Seal, H. L. (1967). The historical development of the Gauss linear model. Biometrika, 54(1/2), 1–24. doi: 10.2307/2333849
- Tufte, E. R. (1983/2001). The visual display of quantitative information (2nd ed.). Cheshire, CT: Graphics Press.
- Wang, Y., & Witten, I. H. (1997). Induction of model trees for predicting continuous classes. Poster papers of the 9th European conference on Machine Learning, Prague, Czech Republic.
- Weingast, B. (2009). Second generation fiscal federalism: The implications of fiscal incentives. Journal of Urban Economics, 65, 279–293. doi: 10.1016/j.jue.2008.12.005
- Witten, I. H., Frank, E., & Hall, M. A. (2011). Data mining: Practical machine learning tools and techniques. New York, NY: Morgan Kaufmann.
- Zhao, K., Ward, M. O., Rundensteiner, E. A., & Higgings, H. N. (2014). LoVis: Local pattern visualization for model refinement. Computer Graphics Forum, 33(3), 331–340. doi: 10.1111/cgf.12389