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Correlating point‐referenced radon and areal uranium data arising from a common spatial process

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  • Brian J. Smith
  • Mary Kathryn Cowles

Abstract

Summary. Because exposure to radon gas in buildings is a likely risk factor for lung cancer, estimation of residential radon levels is an important public health endeavour. Radon originates from uranium, and therefore data on the geographical distribution of uranium in the Earth's surface may inform about radon levels. We fit a Bayesian geostatistical model that appropriately combines data on uranium with measurements of indoor home radon in the state of Iowa, thereby obtaining more accurate and precise estimation of the geographic distribution of average residential radon levels than would be possible by using radon data alone.

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  • Brian J. Smith & Mary Kathryn Cowles, 2007. "Correlating point‐referenced radon and areal uranium data arising from a common spatial process," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 56(3), pages 313-326, May.
    • Handle: RePEc:bla:jorssc:v:56:y:2007:i:3:p:313-326
    DOI: 10.1111/j.1467-9876.2007.00579.x
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    Cited by:

    1. Smith, Brian J. & Yan, Jun & Cowles, Mary Kathryn, 2008. "Unified Geostatistical Modeling for Data Fusion and Spatial Heteroskedasticity with R Package ramps," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 25(i10).
    2. repec:jss:jstsof:25:i10 is not listed on IDEAS

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