Home| Journals | Statistics Online Expert | About Us | Contact Us
    About this Journal  | Table of Contents
Untitled Document

[Abstract] [PDF] [HTML] [Linked References]

International Journal of Statistika and Mathematika, ISSN: 2277- 2790 E-ISSN: 2249-8605

Volume 7, Issue 2, September 2013 pp 37-48

Research Article

Bayesian Estimation and Prediction of Exponentiated Weibull Model

 

Shankar Kumar Shrestha1, Vijay Kumar2

1Public Youth Campus, Tribhuvan University, Kathmandu, NEPAL.

2Department of Mathematics and Statistics, DDU Gorakhpur University, Gorakhpur-273009, Uttar Pradesh, INDIA.

 

 

Academic Editor: Dr. Dase R.K.



Linked References

      1. Chen, M. H., Shao, Q. M., “Monte Carlo estimation of Bayesian credible intervals and HPD intervals,” Journal of Computational and Graphical Statistics, 8(1), 69-92, (1999).
      2. Choudhury, A., “A. Simple Derivation of Moments of the Exponentiated Weibull Distribution, Metrika, 62, 17–22, (2005).
      3. Gelfand, A.E., Smith, A.F.M., Sampling based approach to calculating marginal densities,” Journal of the American Statistical Association, 85, 398–409. (1990).
      4. Gelman, A., A Bayesian Formulation of Exploratory Data Analysis and Goodness-of-fit Testing,” International Statistical Review, 71(2), 369-382, (2003).  
      5. Gelman, A., Carlin, J., Stern, H., Rubin, D. Bayesian Data Analysis,” Second Edition, London,  Chapman & Hall, (2004).
      6. Gelman, A., Meng, X.L., Stern, H.S., “Posterior predictive assessment of model fitness via realized discrepancies,” Stat. Sin., 6, 733–807, (1996).
      7. Gupta, A., Mukherjee, B., Upadhyay, S.K., “A Bayes study using Markov Chain Monte Carlo simulation,” Reliability Engineering & System Safety, 93, 1434-1443, (2008).
      8. Hastings, W. K., “Monte Carlo sampling methods using Markov chains and their applications,” Biometrika, 57, 97 –109, (1970).
      9. Jackson, C.H., “Displaying uncertainty with shading,” The American Statistician, 62(4), 340-347, (2008). 
      10. Jaheen, Z.F., Al Harbi, M.M., “Bayesian estimation for the exponentiated Weibull model via Markov Chain Monte Carlo simulation,” Commun. Stat. Simul. Comput., 40, 532-543, (2011).
      11. Jiang, R., Murthy, D.N.P., “Exponentiated Weibull family: A graphical approach, IEEE Transactions on Reliability, 48(1), 68–72, (1999).
      12. Kim, C., Jung, J., Chung, Y., Bayesian estimation for the exponentiated Weibull model under Type II progressive censoring,” Statistical Papers, 52, 53-70, (2011).
      13. Kumar, V., Ligges, U., “reliaR : A package for some probability distributions,” http://cran.r-project.org/web/packages/reliaR/index.html, (2011).
      14. Kumar, V., Ligges, U., Thomas, A., “ReliaBUGS User Manual : A subsystem in OpenBUGS for some statistical models,” Ver. 1.0, OpenBUGS 3.2.1, http://openbugs.info/w/downloads, (2010).
      15. Lunn, D.J., Jackson, C., Best, N., Andrew, A., Spiegelhalter, D., “The BUGS Book :A Practical Introduction to Bayesian Analysis,” Chapman & Hall/CRC, London, UK, (2013).
      16. Metropolis, N., Rosenbluth, A.W., Rosenbluth, M.N., Teller, A.H., Teller, E., “Equations of state calculations by fast computing machines,” Journal Chemical Physics, 21, 1087–1091, (1953).
      17. Mudholkar, G.S., Srivastava, D.K.,  Exponentiated Weibull family for analyzing bathtub failure-rate data,” IEEE Transactions on Reliability, 42(2), 299–302, (1993).
      18. Mudholkar, G.S., Hutson, A.D., “The exponentiated Weibull family: some properties and a flood data application,” Communications in Statistics - Theory and Methods, 25(12), 3059-3083, (1996).
      19. Mudholkar, G.S., Srivastava, D.K., Freimer, M., “The exponentiated Weibull family—a reanalysis of the bus-motor-failure data,” Technometrics, 37(4), 436 – 445, (1995).
      20. Murthy, D.N.P., Xie, M., Jiang, R., “Weibull Models,”  Wiley, New York, (2004).
      21. Nadarajah, S., Kotz, S., “The exponentiated type distributions,” Acta Applicandae Mathematicae, 92, 97-111, (2006).
      22. Nadarajah, S.,Cordeiro, G.M., Edwin M. M. Ortega, E.M.M., The exponentiated Weibull distribution: a survey,” Statistical Papers, DOI 10.1007/s00362-012-0466-x, (2012).
      23. Nassar, M.M., Eissa, F. H., “Bayesian Estimation for the Exponentiated Weibull Model,” Communications in Statistics - Theory and Methods, 33(10), 2343 –2362, (2004).
      24. Nassar, M.M., Eissa, F. H., “On the Exponentiated Weibull Distribution,” Communications in Statistics - Theory and Methods, 32(7), 1317 –1336, (2003).
      25. Nichols, M.D., Padgett, W.J., “A bootstrap control chart for Weibull percentiles,” Quality and Reliability Engineering International, 22, 141-151, (2006).
      26. Ntzoufras, I., “Bayesian Modeling using WinBUGS,” John Wiley & Sons, New York, (2009).
      27. Pal, M., Ali, M.M.,Woo, J., “Exponentiated Weibull Distribution,” Statistica, LXVI, no. 2, 139-147, (2006).
      28. Pham, H., Lai, C.D., “On recent generalizations of the Weibull distribution,” IEEE Transactions on Reliability, 56 (1), 454-458, (2007).
      29. R Development Core Team, “R: A language and environment for statistical computing,” R Foundation for Statistical Computing, Vienna, Austria,  (2013).
      30. Rinne, H., The Weibull Distribution: A Handbook,” CRC Press, London, (2009).
      31. Rizzo, M. L., Statistical computing with R,” Chapman & Hall/CRC, (2008). 
      32. Singh,U., Gupta, P.K., Upadhyay, S.K., Estimation of three- parameter exponentiated-Weibull distribution under type-II censoring,” Journal of Statistical Planning and Inference, vol. 134, 350-372, (2005a).
      33. Singh,U., Gupta, P.K., Upadhyay, S.K., “Estimation of parameters for exponentiated-Weibull family under type-II censoring scheme,” Computational Statistics and Data Analysis, 48, 509 – 523, (2005b).
      34. Thomas, A., O’Hara, B., Ligges, U. and Sturtz, S., “Making BUGS Open,” R News, 6, 12–17, URL http://mathstat.helsinki.fi/openbugs/, (2006).
      35. Thomas,A., “OpenBUGS Developer Manual,” version 3.1.2,  http://www.openbugs.info/, (2010). 
 
 
 
 
 
  Copyrights statperson consultancy www

Copyrights statperson consultancy www.statperson.com  2013. All Rights Reserved.

Developer Details