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Research Article

An extension of Rayleigh distribution and applications

, & | (Reviewing editor)
Article: 1622191 | Received 29 Jan 2019, Accepted 19 May 2019, Published online: 31 May 2019

References

  • Abd Elfattah, A., Hassan, A. S., & Ziedan, D. (2006). Efficiency of maximum likelihood estimators under different censored sampling schemes for Rayleigh distribution. Interstat.
  • Akaike, H. (1974). A new look at the statistical model identification. Selected Papers of Hirotugu Akaike: Springer, 215–16.
  • Al-Aqtash, R., Lee, C., & Famoye, F. (2014). Gumbel-Weibull distribution: Properties and applications. Journal of Modern Applied Statistical Methods, 13, 11. doi:10.22237/jmasm/1414815000
  • Alizadeh, M., Cordeiro, G. M., Pinho, L. G. B., & Ghosh, I. (2017). The Gompertz-G family of distributions. Journal of Statistical Theory and Practice, 11, 179–207. doi:10.1080/15598608.2016.1267668
  • Alzaatreh, A., Lee, C., & Famoye, F. (2012). On the discrete analogues of continuous distributions. Statistical Methodology, 9, 589–603. doi:10.1016/j.stamet.2012.03.003
  • Alzaatreh, A., Lee, C., & Famoye, F. (2013). A new method for generating families of continuous distributions. Metron, 71, 63–79. doi:10.1007/s40300-013-0007-y
  • Alzaatreh, A., Lee, C., & Famoye, F. (2014). T-normal family of distributions: A new approach to generalize the normal distribution. Journal of Statistical Distributions and Applications, 1, 16. doi:10.1186/2195-5832-1-16
  • Bekker, A., Roux, J., & Mosteit, P. (2000). A generalization of the compound Rayleigh distribution: Using a Bayesian method on cancer survival times. Communications in Statistics-Theory and Methods, 29, 1419–1433. doi:10.1080/03610920008832554
  • Best, D. J., Rayner, J. C., & Thas, O. (2010). Easily applied tests of fit for the Rayleigh distribution. Sankhya B, 72, 254–263. doi:10.1007/s13571-011-0011-2
  • Bozdogan, H. (1987). Model selection and Akaike’s information criterion (AIC): The general theory and its analytical extensions. Psychometrika, 52, 345–370. doi:10.1007/BF02294361
  • Cordeiro, G. M., & Lemonte, A. J. (2011). The β-Birnbaum–Saunders distribution: An improved distribution for fatigue life modeling. Computational Statistics & Data Analysis, 55, 1445–1461. doi:10.1016/j.csda.2010.10.007
  • Dey, S. (2009). Comparison of Bayes estimators of the parameter and reliability function for Rayleigh distribution under different loss functions. Malaysian Journal of Mathematical Sciences, 3.
  • Fundi, M. D., Njenga, E. G., & Keitany, K. G. (2017). Estimation of parameters of the two-parameter Rayleigh distribution based on progressive Type-II censoring using maximum likelihood method via the NR and the EM algorithms. American Journal of Theoretical and Applied Statistics, 6, 1–9. doi:10.11648/j.ajtas.20170601.11
  • Hannan, E. J., & Quinn, B. G. (1979). The determination of the order of an autoregression. Journal of the Royal Statistical Society: Series B (Methodological), 41, 190–195.
  • Hosking, J. R. (1990). L-moments: Analysis and estimation of distributions using linear combinations of order statistics. Journal of the Royal Statistical Society Series B (Methodological), 52, 105–124. doi:10.1111/rssb.1990.52.issue-1
  • Kundu, D., & Raqab, M. Z. (2005). Generalized Rayleigh distribution: Different methods of estimations. Computational Statistics & Data Analysis, 49, 187–200. doi:10.1016/j.csda.2004.05.008
  • Mahmoud, M., & Ghazal, M. (2017). Estimations from the exponentiated Rayleigh distribution based on generalized Type-II hybrid censored data. Journal of the Egyptian Mathematical Society, 25, 71–78. doi:10.1016/j.joems.2016.06.008
  • Merovci, F. (2013). Transmuted Rayleigh distribution. Austrian Journal of Statistics, 42, 21–31. doi:10.17713/ajs.v42i1.163
  • Merovci, F. (2014). Transmuted generalized Rayleigh distribution. Journal of Statistics Applications & Probability, 3, 9. doi:10.18576/jsap/030102
  • Merovci, F., & Elbatal, I. (2015). Weibull Rayleigh distribution: Theory and applications. Applied Mathematics & Information Sciences, 9, 2127.
  • Schwarz, G. (1978). Estimating the dimension of a model. The Annals of Statistics, 6, 461–464. doi:10.1214/aos/1176344136
  • Smith, R. L., & Naylor, J. (1987). A comparison of maximum likelihood and Bayesian estimators for the three-parameter Weibull distribution. Applied Statistics, 358–369. doi:10.2307/2347795
  • Tahir, M., Cordeiro, G. M., Alzaatreh, A., Mansoor, M., & Zubair, M. (2016). The Logistic-X family of distributions and its applications. Communications in Statistics-Theory and Methods, 45, 7326–7349. doi:10.1080/03610926.2014.980516
  • Tahir, M., Zubair, M., Mansoor, M., Cordeiro, G. M., Alizadeh, M., & Hamedani, G. (2016). A new Weibull-G family of distributions. Hacettepe Journal of Mathematics and Statistics.
  • Voda, V. G. (2007). A new generalization of Rayleigh distribution. Reliability: Theory & Applications, 2.