Goodness-of-fit Tests for a Semiparametric Model under Random Double Truncation
(2012) , 16 pages
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- Abstract
- Doubly truncated data are commonly encountered in areas like medicine, astronomy, economy, among others. A semiparametric estimator of a doubly truncated random variable has been proposed by Moreira and de Uña-Alvarez (2010b). Their estimator is based on a parametric specification of the distribution function of the truncation times. This semiparametric estimator outperforms the nonparametric maximum likelihood estimator when the parametric information is correct, but might behave badly when the assumed parametric model is far off. In this paper we introduce several goodness-of-fit tests for the parametric model. The proposed tests are investigated through simulations. For illustration purposes, the tests are also applied to data on the induction time to AIDS for blood transfusion patients.
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Citations
Moreira, C., de Uña-Alvarez, J., & Van Keilegom, I. (2012). Goodness-of-fit Tests for a Semiparametric Model under Random Double Truncation (ISBA Discussion Paper 2012/24). https://hdl.handle.net/2078.5/204780