Parameters Estimation Based on Progressively Censored Data from Inverse Weibull Distribution

Mostafa M. MohieEl-Din; Fathy H. Riad; Mohamed A. El-Sayed

doi:doi:10.11648/j.ajtas.20130206.11

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Parameters Estimation Based on Progressively Censored Data from Inverse Weibull Distribution

Mostafa M. MohieEl-Din, Fathy H. Riad, Mohamed A. El-Sayed

Published in American Journal of Theoretical and Applied Statistics (Volume 2, Issue 6)

Received: 4 September 2013 Published: 30 September 2013

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Abstract

In this article, our main aim is to investigate the parameters estimation of inverse Weibull distribution in the frame work of progressively type II. We consider the censored sample from a two parameters inverse Weibull. The point estimators of the parameters derived by using the maximum likelihood method. The exact joint confidence region and confidence interval for the parameters are obtained. A numerical example is provided to illustrate the proposed. estimation methods developed here.

Published in	American Journal of Theoretical and Applied Statistics (Volume 2, Issue 6)
DOI	10.11648/j.ajtas.20130206.11
Page(s)	149-153
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), 2013. Published by Science Publishing Group

Keywords

Joint Confidence Region, Maximum Likelihood Estimator, Progressively Type II Censored Sample, Confidence Interval

References

[1]	A. C. Cohen, Progressively censored samples in life testing. Techno metrics, 5, 327-339, (1963).
[2]	N. R. Mann, Best linear invariant estimation for Weibull parameters under progressive censoring, Technometrics, 13, 521-533, (1971).
[3]	J. Y. Wong, Simultaneously estimating the three Weibull parameters from progressively censored samples, Microelectronics and Reliability, 33, 2217- 2224, (1993).
[4]	N. Balakrishnan, and R. Aggarwala, Progressive Censoring-Theory, Methods, and Applications, Birkhauser, Boston, SBN 978-0-8176-4001-9 e-book package (2000).
[5]	Wu. Shuo-Jye Estimation of the parameters of the weibull distribution with progressively censored data, Journal of Japan Statistical Society, 2, 155-163, (2002).
[6]	W. B. Nelson, Applied Life Data Analysis. John Wiley & Sons, New York, (1982).
[7]	R. Calaria, and G. Pulcini, On the maximum likelihood and least-squares estimation in the inverse Weibull distributions. Statistical Application, 2(1), 53-66, (1990).
[8]	M. Maswedah, Conditional confidence interval estimation for the inverse Weibull distribution based on censored generalized order statistics. Journal of Statisticl Computation and Simulation, 73, 887-898, (2003).
[9]	R. Dumonceaux, and C. E. Antle, Discrimination between the lognormal and Weibull distribution. Techno metrics, 15, 923-926, (1973).
[10]	N. L. Johnson, S. Kotz, and N. Balakrishnan, Continuous Univariate Distributions. Vol. 2, second edition. John Wiley & Sons New York, (1995).
[11]	D. N. P. Murthy, M. Xie, and R. Jiang, Weibull Model. John Wiley & Sons, New York, (2004).
[12]	M. M, Mohie El-Din,,and F. H. Riad, Estimation and Prediction for the Inverse Weibull Distribution Based on Records, Journal of Advanced Research in Statistics and Probability (JARSP), 3(2), 20 – 27, (2011).
[13]	P. Erto, New Practical Bayes estimators for the 2-Parameter Weibull distribution, IEEE Transactions on Reliability R-31, 194-197, (1982),
[14]	M. Marušić, , D. Marković, and D. Jukić , Least squares fitting the three-parameter inverse Weibull density, Math. Commun., Vol. 15, No. 2, pp. 539-553, (2010).
[15]	D. R. Thomas, and W. M. Wilson, Linear order statistic estimation for the two parameter Weibull and extreme value distribution from type-II progressively censored samples, Technometrics, 14, 679-691, (1972).

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APA Style

Mostafa M. MohieEl-Din, Fathy H. Riad, Mohamed A. El-Sayed. (2013). Parameters Estimation Based on Progressively Censored Data from Inverse Weibull Distribution. American Journal of Theoretical and Applied Statistics, 2(6), 149-153. https://doi.org/10.11648/j.ajtas.20130206.11

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ACS Style

Mostafa M. MohieEl-Din; Fathy H. Riad; Mohamed A. El-Sayed. Parameters Estimation Based on Progressively Censored Data from Inverse Weibull Distribution. Am. J. Theor. Appl. Stat. 2013, 2(6), 149-153. doi: 10.11648/j.ajtas.20130206.11

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AMA Style

Mostafa M. MohieEl-Din, Fathy H. Riad, Mohamed A. El-Sayed. Parameters Estimation Based on Progressively Censored Data from Inverse Weibull Distribution. Am J Theor Appl Stat. 2013;2(6):149-153. doi: 10.11648/j.ajtas.20130206.11

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@article{10.11648/j.ajtas.20130206.11,
  author = {Mostafa M. MohieEl-Din and Fathy H. Riad and Mohamed A. El-Sayed},
  title = {Parameters Estimation Based on Progressively Censored Data from Inverse Weibull Distribution},
  journal = {American Journal of Theoretical and Applied Statistics},
  volume = {2},
  number = {6},
  pages = {149-153},
  doi = {10.11648/j.ajtas.20130206.11},
  url = {https://doi.org/10.11648/j.ajtas.20130206.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20130206.11},
  abstract = {In this article, our main aim is to investigate the parameters estimation of inverse Weibull distribution in the frame work of progressively type II. We consider the censored sample from a two parameters inverse Weibull. The point estimators of the parameters derived by using the maximum likelihood method. The exact joint confidence region and confidence interval for the parameters are obtained. A numerical example is provided to illustrate the proposed. estimation methods developed here.},
 year = {2013}
}

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TY  - JOUR
T1  - Parameters Estimation Based on Progressively Censored Data from Inverse Weibull Distribution
AU  - Mostafa M. MohieEl-Din
AU  - Fathy H. Riad
AU  - Mohamed A. El-Sayed
Y1  - 2013/09/30
PY  - 2013
N1  - https://doi.org/10.11648/j.ajtas.20130206.11
DO  - 10.11648/j.ajtas.20130206.11
T2  - American Journal of Theoretical and Applied Statistics
JF  - American Journal of Theoretical and Applied Statistics
JO  - American Journal of Theoretical and Applied Statistics
SP  - 149
EP  - 153
PB  - Science Publishing Group
SN  - 2326-9006
UR  - https://doi.org/10.11648/j.ajtas.20130206.11
AB  - In this article, our main aim is to investigate the parameters estimation of inverse Weibull distribution in the frame work of progressively type II. We consider the censored sample from a two parameters inverse Weibull. The point estimators of the parameters derived by using the maximum likelihood method. The exact joint confidence region and confidence interval for the parameters are obtained. A numerical example is provided to illustrate the proposed. estimation methods developed here.
VL  - 2
IS  - 6
ER  -

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Author Information

Mostafa M. MohieEl-Din

Dept. of Mathematics, Faculty of Science, Al-Azhar University, Egypt
Fathy H. Riad

Dept. of Mathematics, Faculty of Science, Minia University, Egypt
Mohamed A. El-Sayed

Dept. of Mathematics, Faculty of Science in Qena, South Valley University, Egypt

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APA Style

Mostafa M. MohieEl-Din, Fathy H. Riad, Mohamed A. El-Sayed. (2013). Parameters Estimation Based on Progressively Censored Data from Inverse Weibull Distribution. American Journal of Theoretical and Applied Statistics, 2(6), 149-153. https://doi.org/10.11648/j.ajtas.20130206.11

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ACS Style

Mostafa M. MohieEl-Din; Fathy H. Riad; Mohamed A. El-Sayed. Parameters Estimation Based on Progressively Censored Data from Inverse Weibull Distribution. Am. J. Theor. Appl. Stat. 2013, 2(6), 149-153. doi: 10.11648/j.ajtas.20130206.11

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AMA Style

Mostafa M. MohieEl-Din, Fathy H. Riad, Mohamed A. El-Sayed. Parameters Estimation Based on Progressively Censored Data from Inverse Weibull Distribution. Am J Theor Appl Stat. 2013;2(6):149-153. doi: 10.11648/j.ajtas.20130206.11

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@article{10.11648/j.ajtas.20130206.11,
  author = {Mostafa M. MohieEl-Din and Fathy H. Riad and Mohamed A. El-Sayed},
  title = {Parameters Estimation Based on Progressively Censored Data from Inverse Weibull Distribution},
  journal = {American Journal of Theoretical and Applied Statistics},
  volume = {2},
  number = {6},
  pages = {149-153},
  doi = {10.11648/j.ajtas.20130206.11},
  url = {https://doi.org/10.11648/j.ajtas.20130206.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20130206.11},
  abstract = {In this article, our main aim is to investigate the parameters estimation of inverse Weibull distribution in the frame work of progressively type II. We consider the censored sample from a two parameters inverse Weibull. The point estimators of the parameters derived by using the maximum likelihood method. The exact joint confidence region and confidence interval for the parameters are obtained. A numerical example is provided to illustrate the proposed. estimation methods developed here.},
 year = {2013}
}

Copy | Download

TY  - JOUR
T1  - Parameters Estimation Based on Progressively Censored Data from Inverse Weibull Distribution
AU  - Mostafa M. MohieEl-Din
AU  - Fathy H. Riad
AU  - Mohamed A. El-Sayed
Y1  - 2013/09/30
PY  - 2013
N1  - https://doi.org/10.11648/j.ajtas.20130206.11
DO  - 10.11648/j.ajtas.20130206.11
T2  - American Journal of Theoretical and Applied Statistics
JF  - American Journal of Theoretical and Applied Statistics
JO  - American Journal of Theoretical and Applied Statistics
SP  - 149
EP  - 153
PB  - Science Publishing Group
SN  - 2326-9006
UR  - https://doi.org/10.11648/j.ajtas.20130206.11
AB  - In this article, our main aim is to investigate the parameters estimation of inverse Weibull distribution in the frame work of progressively type II. We consider the censored sample from a two parameters inverse Weibull. The point estimators of the parameters derived by using the maximum likelihood method. The exact joint confidence region and confidence interval for the parameters are obtained. A numerical example is provided to illustrate the proposed. estimation methods developed here.
VL  - 2
IS  - 6
ER  -

Copy | Download