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Prediction Intervals for Progressive Type-II Right-Censored Order Statistics from Two Independent Sequences

Received: 18 March 2015     Accepted: 29 March 2015     Published: 3 August 2015
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Abstract

This article discusses the problem of predicting future progressive Type-II right censored order statistics based on progressive Type-II right-censored, ordered statistics, record values and current records that observed from the past X-sequence. Such coverage probabilities of the prediction intervals are exact and don’t depend on the sampling distribution F. Finally, a real life time data were given to breakdown the insulating fluid between electrodes which is used to illustrate the derived results.

Published in American Journal of Theoretical and Applied Statistics (Volume 4, Issue 5)
DOI 10.11648/j.ajtas.20150405.13
Page(s) 329-338
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2015. Published by Science Publishing Group

Keywords

Prediction Intervals, Progressive Censoring, Order Statistics, Records, Coverage Probability, Prediction Coefficient

References
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[4] J. Ahmadi, N. Balakrishnan, outer and inner prediction intervals for order statistics based on current records, Springer, 53 (2012) 789– 802.
[5] M. Z. Raqab, N. Balakrishnan, Prediction intervals for future records, Stat. Prob. Letters, 78 (2008) 1955 – 1963.
[6] J. Ahmadi, N. Balakrishnan, Prediction of order statistics and record values from two independent sequences, Statistics, 44 (2010) 417– 430.
[7] J. Ahmadi, N. Balakrishnan, Distribution-free prediction intervals for order statistics based on record coverage, J. Korean Stat. Society, 40 (2011) 181 – 192.
[8] J. Ahmadi, S.M.T.K. MirMostafaee, N. Balakrishnan, Nonparametric prediction intervals for future record intervals based on order statistics, Stat. Prob. Letters, 80 (2010) 1663 – 1672.
[9] M.Z. Raqab, Distribution-free prediction intervals for the future current record statistics, Springer, 50 (2009) 429– 439.
[10] M. Z. Raqab, N. Balakrishnan, Prediction intervals for future records, Stat. Prob. Letters, 78 (2008) 1955 – 1963.
[11] M. M. Mohie El-Din, M. S. Kotb, W. S. Emam, Prediction intervals for future order statistics from two independent sequences, AJTAS, 4 (2015) 33 – 40.
[12] U. Kamps, E. Cramer, On distributions of generalized order statistics, Statistics, 35 (2001) 269 – 280.
[13] E. Basiri, M. Z. Raqab, Nonparametric prediction intervals for progressive Type-II censored order statistics based on k-records, Springer, 28 (2013) 2825 – 2848.
[14] R. Aggarwala, N. Balakrishnan, Progressive censoring: theory,methods, and applications. Birkhäuser, Boston (2000).
[15] N. Balakrishnan, Progressive censoring methodology: an appraisal, Springer, 16 (2007) 211 – 259.
[16] N. Balakrishnan, A. Childs, B. Chandrasekar, An efficient computational method for moments of order statistics under progressive censoring, Stat. Prob. Letters, 60 (2002) 359 – 365.
[17] B.C. Arnold, N. Balakrishnan, H.N. Nagaraja, A First Course in Order Statistics, John Wiley - Sons, New York, (1992).
[18] V.B. Nevzorov, Records, Mathematical Theory (English Translation), American Mathematical Society, Providence,, (2000).
[19] S. Gulati, W.J. Padgett, Parametric and Nonparametric Inference from Record-Breaking Data,Springer-Verlag, New York, (2003).
[20] M. Ahsanullah, Record Values — Theory and Applications, University Press of America Inc., New York, (2004).
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Cite This Article
  • APA Style

    M. M. Mohie El-Din, M. S. Kotb, W. S. Emam. (2015). Prediction Intervals for Progressive Type-II Right-Censored Order Statistics from Two Independent Sequences. American Journal of Theoretical and Applied Statistics, 4(5), 329-338. https://doi.org/10.11648/j.ajtas.20150405.13

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    ACS Style

    M. M. Mohie El-Din; M. S. Kotb; W. S. Emam. Prediction Intervals for Progressive Type-II Right-Censored Order Statistics from Two Independent Sequences. Am. J. Theor. Appl. Stat. 2015, 4(5), 329-338. doi: 10.11648/j.ajtas.20150405.13

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    AMA Style

    M. M. Mohie El-Din, M. S. Kotb, W. S. Emam. Prediction Intervals for Progressive Type-II Right-Censored Order Statistics from Two Independent Sequences. Am J Theor Appl Stat. 2015;4(5):329-338. doi: 10.11648/j.ajtas.20150405.13

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  • @article{10.11648/j.ajtas.20150405.13,
      author = {M. M. Mohie El-Din and M. S. Kotb and W. S. Emam},
      title = {Prediction Intervals for Progressive Type-II Right-Censored Order Statistics from Two Independent Sequences},
      journal = {American Journal of Theoretical and Applied Statistics},
      volume = {4},
      number = {5},
      pages = {329-338},
      doi = {10.11648/j.ajtas.20150405.13},
      url = {https://doi.org/10.11648/j.ajtas.20150405.13},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20150405.13},
      abstract = {This article discusses the problem of predicting future progressive Type-II right censored order statistics based on progressive Type-II right-censored, ordered statistics, record values and current records that observed from the past X-sequence. Such coverage probabilities of the prediction intervals are exact and don’t depend on the sampling distribution F. Finally, a real life time data were given to breakdown the insulating fluid between electrodes which is used to illustrate the derived results.},
     year = {2015}
    }
    

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    AU  - M. M. Mohie El-Din
    AU  - M. S. Kotb
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    T2  - American Journal of Theoretical and Applied Statistics
    JF  - American Journal of Theoretical and Applied Statistics
    JO  - American Journal of Theoretical and Applied Statistics
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    AB  - This article discusses the problem of predicting future progressive Type-II right censored order statistics based on progressive Type-II right-censored, ordered statistics, record values and current records that observed from the past X-sequence. Such coverage probabilities of the prediction intervals are exact and don’t depend on the sampling distribution F. Finally, a real life time data were given to breakdown the insulating fluid between electrodes which is used to illustrate the derived results.
    VL  - 4
    IS  - 5
    ER  - 

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Author Information
  • Department of Mathematics, Faculty of Science, Al-Azhar, University, Nasr City, Cairo, Egypt

  • Department of Mathematics, Faculty of Science, Al-Azhar, University, Nasr City, Cairo, Egypt

  • Department of Basic Science, Faculty of Engineering, British, University in Egypt, Al-Shorouq City, Cairo, Egypt

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