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Journals / Istatistik Journal of The Turkish Statistical Association / 2018 / Cilt: 11 Sayı: 1-2

BAYESIAN PREDICTION OF PROGRESSIVELY FIRST-FAILURE-CENSORED ORDER STATISTICS BASED ON k-RECORD VALUES FROM WEIBULL DISTRIBUTION

Mohammad Vali AHMADİ
Mahdi DOOSTPARAST
Pages
12–28
Publication Date
2018-01-01
DOI
—
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Finally, the estimated risks of various point predictors obtained are compared using the Monte Carlo method.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Prediction on the basis of censored data has an important role in lifetime studies.
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Key Findings & Data:This paper discusses Bayesian two-sample prediction of progressively firrst-failure-censored order statistics coming from a future sample based on observed k-record values from two-parameter Weibull distribution.
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Conclusion & Impact:Finally, the estimated risks of various point predictors obtained are compared using the Monte Carlo method.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Bayesian prediction · k-record · Progressive first-failure censoring

Abstract

Prediction on the basis of censored data has an important role in lifetime studies. This paper discusses Bayesian two-sample prediction of progressively firrst-failure-censored order statistics coming from a future sample based on observed k-record values from two-parameter Weibull distribution. Bayesian interval predictions are obtained based on a continuous-discrete joint prior for the unknown two parameters. Moreover, Bayesian point predictors are investigated under symmetric and asymmetric loss functions. Finally, the estimated risks of various point predictors obtained are compared using the Monte Carlo method.

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Cite This Article

AHMADİ, M. V., DOOSTPARAST, M. (2018). BAYESIAN PREDICTION OF PROGRESSIVELY FIRST-FAILURE-CENSORED ORDER STATISTICS BASED ON k-RECORD VALUES FROM WEIBULL DISTRIBUTION. Istatistik Journal of The Turkish Statistical Association, Cilt: 11 Sayı: 1-2, 12–28. https://ajindex.com/articles/938150

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References (14)

  1. Ahmadi, J., MirMostafaee, S.M.T.K. and Balakrishnan, N. (2011). Bayesian Prediction of order statistics based on k-record values from exponential distribution. Statistics, 45, 375-387.
  2. Ahmadi, J., MirMostafaee, S.M.T.K. and Balakrishnan, N. (2012). Bayesian Prediction of k-record values based on progressively censored data from exponential distribution. Journal of Statistical Computation and Simulation, 82, 51-62.
  3. Ali Mousa, M.A.M. and Jaheen, Z.F. (2002). Bayesian prediction for progressively censored data from the Burr model. Statistical Papers, 43, 587-593.
  4. Ali Mousa, M.A.M. and Al-Sagheer, S.A. (2005). Bayesian prediction for progressively Type-II censored data from the Rayleigh model. Communications in Statistics - Theory and Methods, 34, 2353-2361.
  5. Arnold, B.C., Balakrishnan, N. and Nagaraja, H.N. (1998).
  6. Records, John Wiley & Sons, New York. [6] Balakrishnan, N. (2007). Progressive censoring methodology: an appraisal. Test, 16, 211-256.‌
  7. Balakrishnan, N. and Aggarwala, R. (2000). Progressive Censoring: Theory, Methods and Applications, Birkh¨auser, Boston. Balakrishnan, N. and Cramer, E. (2014). The Art of Progressive Censoring: Applications to Reliability and Quality, Birkh¨auser, New York. Balakrishnan, N. and Shafay, R.A. (2012). One- and two-sample Bayesian prediction intervals based on Type-II hybrid censored data. Communications in Statistics - Theory and Methods, 41, 1511-1531.
  8. Calabria, R. and Pulcini, G. (1996). Point estimation under asymmetric loss functions for left-truncated exponential samples. Communications in Statistics - Theory and Methods, 25, 585-600.
  9. Doostparast, M. (2009). A note on estimation based on record data. Metrika, 69, 69-80.
  10. Dunsmore, I.R. (1983). The future occurrence of records. Annals of the Institute of Statistical Mathe- matics, 35, 267-277.
  11. Dziubdziela, W. and Kopocinski, B. (1976). Limiting properties of the k-th record values. Zastosowania Matematyki, 15, 187-190.
  12. Ghafoori, S., Habibi Rad, A. and Doostparast, M. (2011). Bayesian two-sample prediction with progres- sively Type-II censored data for some lifetime models. Journal of Iranian Statistical Society, 10, 63-86.
  13. Huang, S.R. and Wu, S.J. (2012). Bayesian estimation and prediction for Weibull model with progressive censoring. Journal of Statistical Computation and Simulation, 82, 1607-1620.
  14. Kamps, U. (1995). A concept of generalized order statistics, Teubner, Stuttgart. Kamps, U. (1995). A concept of generalized order statistics. Journal of Statistical Pla