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Model selection in radon data fusion

Author

Listed:
  • Zhang Xuze

    (Department of Mathematics and Institute for Systems Research, University of Maryland, College Park. United States)

  • Pyne Saumyadipta

    (Public Health Dynamics Laboratory, Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh. United States)

  • Kedem Benjamin

    (Department of Mathematics and Institute for Systems Research, University of Maryland, College Park. United States)

Abstract

Fitting parametric models or the use of the empirical cumulative distribution function are problematic when it comes to the estimation of tail probabilities from small samples. A possible remedy is to fuse or combine the small samples with additional data from external sources and base the inference on the so called density ratio model with variable tilt functions, which widens the support of the estimated distribution of interest. This approach is illustrated using residential radon concentration data collected from western Pennsylvania.

Suggested Citation

  • Zhang Xuze & Pyne Saumyadipta & Kedem Benjamin, 2020. "Model selection in radon data fusion," Statistics in Transition New Series, Polish Statistical Association, vol. 21(4), pages 159-165, August.
    • Handle: RePEc:vrs:stintr:v:21:y:2020:i:4:p:159-165:n:1
    DOI: 10.21307/stattrans-2020-036
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