Skip to main content
Log in

Estimation of \(P(Y > X)\) for the Weibull distribution

  • Original Article
  • Published:
International Journal of System Assurance Engineering and Management Aims and scope Submit manuscript

Abstract

The estimation of \(P(Y > X)\) is studied when X and Y are independent Weibull random variables taking arbitrary parameter values. Three point and three interval estimators are derived. Their performance with respect to relative biases, relative mean squared errors, coverage probabilities, and coverage lengths is assessed by simulation studies and a real data application.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  • Asgharzadeh A, Kazemi M, Kundu D (2015) Estimation of \(P(X>Y)\) for Weibull distribution based on hybrid censored samples. Int J Syst Assur Eng Manag. doi:10.1007/s13198-015-0390-2

    Google Scholar 

  • Badar MG, Priest AM (1982) Statistical aspects of fiber and bundle strength in hybrid composites. In: Hayashi T, Kawata K, Umekawa S (eds) Progress in science and engineering composites ICCM-IV, Tokyo, pp 1129–1136

  • Baklizi A (2012) Inference on \(\Pr (X < Y)\) in the two-parameter Weibull model based on records. Int Sch Res Netw Prob Stat. doi:10.5402/2012/263612 (Article ID 263612)

  • Barndorff-Nielsen OE (1986) Inference on full and partial parameters, based on the standardized signed log-likelihood ratio. Biometrika 73:307–322

    MATH  MathSciNet  Google Scholar 

  • Barndorff-Nielsen OE (1991) Modified signed log-likelihood ratio. Biometrika 78:557–563

    Article  MATH  MathSciNet  Google Scholar 

  • Brown GG, Rutemiller HC (1973) Evaluation of \(\Pr \left\lbrace x \le y \right\rbrace \) when both \(X\) and \(Y\) are from three-parameter Weibull distributions. IEEE Trans Reliab R–22:78–82

    Article  MathSciNet  Google Scholar 

  • Chen M-H, Shao Q-M (1999) Monte Carlo estimation of Bayesian credible and HPD intervals. J Comput Graph Stat 8:69–92

    MathSciNet  Google Scholar 

  • Davison AC (2003) Statistical models. Cambridge University Press, Cambridge

    Book  MATH  Google Scholar 

  • Devroye L (1984) A simple algorithm for generating random variates with a log-concave density. Computing 33:247–257

    Article  MATH  MathSciNet  Google Scholar 

  • Efron, B. (1982). The Jackknife, the Bootstrap and Other Resampling Plans. CBMS-NSF regional conference series in applied mathematics, volume 38, Society for Industrial and Applied Mathematics, Philadelphia, Pennsylvania

  • Greco L, Ventura L (2011) Robust inference for the stress-strength reliability. Stat Pap 52:773–788

    Article  MATH  MathSciNet  Google Scholar 

  • Jia X, Guo B (2016) Analysis of non-repairable cold-standby systems in Bayes theory. J Stat Comput Simul 86:2089–2112

    Article  MathSciNet  Google Scholar 

  • Jia X, Wang D, Jiang P, Guo B (2016) Inference on the reliability of Weibull distribution with multiply type-I censored data. Reliab Eng Syst Saf 150:171–181

    Article  Google Scholar 

  • Kilbas AA, Srivastava HM, Trujillo JJ (2006) Theory and applications of fractional differential equations. Elsevier, Amsterdam

    MATH  Google Scholar 

  • Kotz S, Lumelskii Y, Pensky M (2003) The stress-strength model and its generalizations: theory and applications. World Scientific, Singapore

    Book  MATH  Google Scholar 

  • Kundu D (2016) On Bayesian inference of \(P(Y < X)\) for Weibull distribution. In: Chaubey YP (ed) Statistical modelling of survival, reliability and environmental data. Springer, New York

    Google Scholar 

  • Kundu D, Gupta RD (2006) Estimation of \(P[Y < X]\) for Weibull distributions. IEEE Trans Reliab 55:270–280

    Article  Google Scholar 

  • Kundu D, Raqab MZ (2009) Estimation of \(R = P(Y < X)\) for three-parameter Weibull distribution. Stat Prob Lett 79:1839–1846

    Article  MATH  MathSciNet  Google Scholar 

  • Mathai AM, Saxena RK (1978) The \(H\)-function with applications in statistics and other disciplines. Wiley, New York

    MATH  Google Scholar 

  • Srivastava HM, Gupta KC, Goyal SP (1982) The \(H\)-functions of one and two variables with applications. South Asian Publishers, New Delhi

    MATH  Google Scholar 

  • Valiollahi R, Asgharzadeh A, Raqab MZ (2013) Estimation of \(P(Y < X)\) for Weibull distribution under progressive type-II censoring. Commun Stat Theory Methods 42:4476–4498

    Article  MATH  MathSciNet  Google Scholar 

  • Wright EM (1935) The asymptotic expansion of the generalized hypergeometric function. J Lond Math Soc 10:286–293

    Article  MATH  Google Scholar 

Download references

Acknowledgements

The authors thank the editor and the two referees for their helpful comments, which contributed greatly to improve this paper.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Saralees Nadarajah.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Nadarajah, S., Jia, X. Estimation of \(P(Y > X)\) for the Weibull distribution. Int J Syst Assur Eng Manag 8 (Suppl 2), 1762–1774 (2017). https://doi.org/10.1007/s13198-017-0666-9

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13198-017-0666-9

Keywords

Navigation