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Regionalization of multiscale spatial processes by using a criterion for spatial aggregation error

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  • Jonathan R. Bradley
  • Christopher K. Wikle
  • Scott H. Holan

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  • Jonathan R. Bradley & Christopher K. Wikle & Scott H. Holan, 2017. "Regionalization of multiscale spatial processes by using a criterion for spatial aggregation error," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(3), pages 815-832, June.
    • Handle: RePEc:bla:jorssb:v:79:y:2017:i:3:p:815-832
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    File URL: http://hdl.handle.net/10.1111/rssb.12179
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    References listed on IDEAS

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    1. Juan C. Duque & Luc Anselin & Sergio J. Rey, 2012. "The Max-P-Regions Problem," Journal of Regional Science, Wiley Blackwell, vol. 52(3), pages 397-419, August.
    2. Noel Cressie & Gardar Johannesson, 2008. "Fixed rank kriging for very large spatial data sets," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 70(1), pages 209-226, February.
    3. Kolaczyk, Eric D. & Ju, Junchang & Gopal, Sucharita, 2005. "Multiscale, Multigranular Statistical Image Segmentation," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 1358-1369, December.
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    Cited by:

    1. Daniel H. Weinberg & John M. Abowd & Robert F. Belli & Noel Cressie & David C. Folch & Scott H. Holan & Margaret C. Levenstein & Kristen M. Olson & Jerome P. Reiter & Matthew D. Shapiro & Jolene Smyth, 2017. "Effects of a Government-Academic Partnership: Has the NSF-Census Bureau Research Network Helped Improve the U.S. Statistical System?," Working Papers 17-59r, Center for Economic Studies, U.S. Census Bureau.
    2. James Gaboardi, 2020. "Validating Abstract Representations of Spatial Population Data while considering Disclosure Avoidance," Working Papers 20-5, Center for Economic Studies, U.S. Census Bureau.
    3. James Gaboardi, 2020. "Validating Abstract Representations of Spatial Population Data while considering Disclosure Avoidance," Working Papers 20-05, Center for Economic Studies, U.S. Census Bureau.
    4. Harrison Quick & Scott H. Holan & Christopher K. Wikle, 2018. "Generating partially synthetic geocoded public use data with decreased disclosure risk by using differential smoothing," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 181(3), pages 649-661, June.
    5. Duncan Lee & Craig Anderson, 2023. "Delivering spatially comparable inference on the risks of multiple severities of respiratory disease from spatially misaligned disease count data," Biometrics, The International Biometric Society, vol. 79(3), pages 2691-2704, September.

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