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Anderson/Titterington (1997). Spatial Clustering

Anderson, N.H. and Titterington, D.M. (1997). Some methods for investigating spatial clustering, with epidemiological applications. Journal of the Royal Statistical Society, Series A, 160(1):87-105.

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Berke (2004). Kriging of Spatial Risk Function

Berke, Olaf. (2004) Exploratory disease mapping: Kriging the spatial risk function from regional count data. International Journal of Health Geographics, 3:18.

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Bonetti/Pagano (2005). Interpoint Distance Distribution

Bonetti, M. and Pagano, M. (2005). The interpoint distance distribution as a descriptor of point patterns, with an application to spatial disease clustering. Statistics in Medicine, 24:753-773.

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Conley et al (2005). Genetic Approach Cluster Detection

Conley, J., Gahegen, M., and Macgill, J. (2005). A genetic approach to detecting clusters in point data sets. Geographical Analysis, 37:286-314.

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Hansen (1991). Headbanging & Robust Smoothing

Hansen, K. M. (1991). Head-banging: Robust smoothing in the plane. IEEE Transactions on Geoscience and Remote Sensing, 29(3):369-378.

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Lawson (2001). Small Scale Disease Clustering

Lawson, A. B. (2001). Small scale: Disease clustering, In: Lawson, A. B. Statistical methods in spatial epidemiology, John Wiley & Sons, ch. 6, pp.103-121.

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Lawson (2002). Spatial Cluster Modeling

Lawson, A. B. (2002). Spatial Cluster Modeling: An Overview, In: Lawson, A. B. and Denison, D. G.T. (eds.), Spatial Cluster Modelling, Champman & Hall/CRC, ch1, pp.1-19.

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Okabe et al (1995). Points on a Network

Okabe, A., Yomono, H., and Kitamura, M. (1995). Statistical analysis of the distribution of points on a network. Geographical Analysis, 27(2):152-175.

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Okabe/Yamada (2001). K-Function on a Network

Okabe, A. and Yamada, I. (2001). The k-function method on a network and its computational implementation. Geographical Analysis, 33(3):271-290.

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Ozonoff et al (2005). Cluster Methods Applied

Ozonoff, A., Webster, T., Vieira, V., Weinberg, J., Ozonoff, D., and Aschengrau, A. (2005). Cluster detection methods applied to the upper Cape Cod cancer data. Environmental Health: A Global Access Science Source, 4(19).

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Rafalski/Zun (2004). GIS & Emergency Room Use

Rafalski, E. and Zun, L. (2004). Using GIS to monitor emergency room use in a large urban hospital in Chicago, Journal of Medical Systems 28, 311(319).

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Shen/Louis (1999). Smoothing By Roughening Approach

Shen, W. and Louis, T. A. (1999). Empirical Bayes estimation via the smoothing by roughening approach. Journal of Computational and Graphical Statistics, 8(4):800-823.

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Sinha/Mark (2005). Similarities in GeoSpatial Lifelines

Sinha, G. and Mark, D. M. (2005). Measuring similarity between geospatial lifelines in studies of environmental health. Journal of Geographical Systems, 7:115-136.

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Waller/Gotway (2004). Spatial Clusters of Events

Waller, L. A. and Gotway, C. A., (2004). Spatial clusters of health events: Point data for cases and controls, In: Waller, L. A. and Gotway, C. A. (2004). Applied spatial statistics for public health data, John Wiley & Sons, ch6, pp.155-199.

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Williamson et al (1998). Bandwidths in Kernel Estimation

Williamson, D., McLafferty, S., Goldsmith, V., McGuire, P., and Mollenkopf, J. (1998). Smoothing crime incident data: New methods for determining the bandwidth in kernel estimation. ESRI User Conference 1998.

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Yamada/Thill (2005). Network-Constrained Clusters

Yamada, I. and Thill, J-C. (2005). Local indicators of network-constrained clusters in spatial point patterns. TBA.

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Yang et al (2004). Improving Geocoding

Yang, D.-H., Bilaver, L. M., Hayes, O., and George, R. (2004). Improving geocoding practices: Evaluation of geocoding tools, Journal of Medical Systems 28, 361(370).

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