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Some Estimation Techniques in Reliability and Survival Analysis Based on Record-Breaking Data

  • Inmaculada Barranco-ChamorroEmail author
  • Sneh Gulati
Conference paper
Part of the Springer Proceedings in Mathematics & Statistics book series (PROMS, volume 136)

Abstract

In this paper we review some of the classical and Bayesian results on statistical inference from records that can be used in reliability and survival analysis. We focus on some important lifetime models, giving special attention to heavy-tailed distributions in order to consider applications of record-breaking data to the study of extreme events. Results on the estimation of the number of observations needed to attain a given number of records are also studied in depth. Numerical illustrations and results on the estimation of cost functions are included as well. This chapter can serve as a guide for people interested in making inferences in the fields of reliability and survival analysis when only record values are available.

Keywords

Record values Heavy tailed distributions Classical inference Bayesian inference Sample-size estimation 

Notes

Acknowledgments

The authors thank the referees for their constructive suggestions, which helped to improve the presentation of the paper. Barranco-Chamorro’s research was supported by grant UJA2013/08/01.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Departamento de Estadistica e I.O. Facultad de MatematicasUniversidad de SevillaSevillaSpain
  2. 2.Department of Mathematics and StatisticsFlorida International UniversityMiamiUSA

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