Out-of-Sample Fusion in Risk Prediction
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.
KeywordsMortality Density ratio model Threshold probabilities Tilt Semiparametric Coverage
AMS Subject ClassificationPrimary: 62F40 Secondary: 62F25
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- Lu, G. 2007. Asymptotic theory for multiple-sample semiparametric density ratio models and its application to mortality forecasting. PhD dissertation, Department of Mathematics, University of Maryland, College Park, MD.Google Scholar