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Journal of Statistical Theory and Practice

, Volume 8, Issue 3, pp 444–459 | Cite as

Out-of-Sample Fusion in Risk Prediction

  • Myron Katzoff
  • Wen Zhou
  • Diba Khan
  • Guanhua Lu
  • Benjamin Kedem
Article

Abstract

The probability that mortality from certain causes exceeds high thresholds is addressed. An out-of-sample fusion method is presented where an original real data sample is fused or combined with independent computer-generated samples in the estimation of exceedance probabilities assuming a density ratio model. Since the size of the combined sample of real and artificial data is larger than that of the real sample, the fused sample produces short confidence intervals relative to traditional methods. Numerical results show that the method maintains good coverage even for some misspecified cases.

Keywords

Mortality Density ratio model Threshold probabilities Tilt Semiparametric Coverage 

AMS Subject Classification

Primary: 62F40 Secondary: 62F25 

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Copyright information

© Grace Scientific Publishing 2014

Authors and Affiliations

  • Myron Katzoff
    • 1
  • Wen Zhou
    • 2
  • Diba Khan
    • 1
  • Guanhua Lu
    • 2
  • Benjamin Kedem
    • 1
    • 2
  1. 1.CDC/National Center for Health StatisticsHyattsvilleUSA
  2. 2.Department of MathematicsUniversity of MarylandCollege ParkUSA

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