One- and Two-Sample Prediction Based on Doubly Censored Exponential Data and Prior Information

• Autores: Arturo Fernández
• Localización: Test: An Official Journal of the Spanish Society of Statistics and Operations Research, ISSN-e 1863-8260, ISSN 1133-0686, Vol. 13, Nº. 2, 2004, págs. 403-416
• Idioma: inglés
• DOI: 10.1007/bf02595779
• Texto completo no disponible (Saber más ...)
• Resumen

  • On the basis of a doubly censored sample from an exponential lifetime distribution, the problem of predicting the lifetimes of the unfailed items (one-sample prediction), as well as a second independent future sample from the same distribution (two-sample prediction), is addressed in a Bayesian setting. A class of conjugate prior distributions, which includes Jeffreys' prior as a special case, is considered. Explicit expressions for predictive densities and survivals are derived. Assuming squared-error loss, Bayes predictive estimators are obtained in closed forms (in particular, the estimator of the number of failures in a specified future time interval is given analytically). Bayes prediction limits and predictive estimators under absolute-error loss can readily be computed using iterative methods. As applications, the total duration time in a life test and the failure time of a {\it k-out-of-n} system may be predicted. As an illustration, a numerical example is also included.