A New Extended Burr XII Distribution


  • Indranil Ghosh University of North carolina, Wilmington
  • Marcelo Bourguinon Universidade Federal do Rio Grande do Norte, Natal-RN, Brazil




In this paper, we propose a new lifetime distribution, namely the extended Burr XII distribution (using the technique as mentioned in Cordeiro et al. (2015)). We derive some basic properties of the new distribution and provide a Monte Carlo simulation study to evaluate the maximum likelihood estimates of model parameters. For illustrative purposes, two real life data sets have been considered as an application of the proposed model.

Author Biographies

Indranil Ghosh, University of North carolina, Wilmington

Ph.D (Applied Statistics)

Assistant Professor of Statistics

Department of Mathematics and Statistics

University of North Carolina, Wilmington



Marcelo Bourguinon, Universidade Federal do Rio Grande do Norte, Natal-RN, Brazil

Assistant Professor of Statistics

Universidade Federal do Rio Grande do Norte, Natal-RN, Brazil


Arnold, B.C., Balakrishnan, N and Nagaraja, H.N. (2008). A First Course in Order Statistics, Classic edition. Society for Industrial and Applied Mathematics, Philadelphia, PA.

Coredeiro, M. G., Alizadeh, M. and Marinho, D. P. (2015). The type I half - logistic family of distributions, Journal of Statistical Computation and Simulation, DOI: 10.1080/00949655.2015.1031233.

Glanzel, W. (1987). A characterization theorem based on truncated moments and its ap- plication to some distribution families, Mathematical Statistics and Probability Theory. Bad Tatzmannsdorf, B, 75-84.

Glanzel, W. (1990). Some consequences of a characterization theorem based on truncated moments. Statistics, 21, 613-618.

Glanzel, W. and Hamedani, G.G. (2001). Characterizations of univariate continuous distributions. Studia Sci. Math. Hungar., 37, 83-118.

Hall, I.J. (1984). Approximate one-sided tolerance limits for the difference or sum of two independent normal variates. Journal of Qualitative Technology, 16,15-19.

Hamedani, G.G. (2010). Characterizations of univariate continuous distributions III. Studia Scientiarum Mathematicarum Hungarica, 43, 361-385.

Hamedani, G.G. (2013). On certain generalized gamma convolution distributions. Technical Report, No. 484, MSCS, Marquette University.

Lai, C. D., Xie, M. and Murthy, DNP. (2003). A modified Weibull distribution. IEEE Trans- actions on Reliability, 52, 3-7.

Mudholkar, G. S. & Huston, A. D. (1996). The exponentiated Weibull family: some properties and a flood data application. Communications in Statistics -Theory and Methods, 25, 3059- 3083.

Mudholkar, G. S. & Kollia, G. D. (1994). Generalized Weibull family: a structural analysis. Communications in Statistics - Theory and Methods, 23, 1149-1171.

Mudholkar, G. S. & Srivastava, D. K. (1993). Exponentiated Weibull family analyzing bathtub failure-rate data. IEEE Transactions and Reliability, 42, 299-302.

Mudholkar, G. S., Srivastava, D. K. & Freimer, M. (1995). The exponentiated Weibull family. Technometrics, 37, 436-445.

Mudholkar, G. S., Srivastava, D. K. & Kollia, G. D. (1996). A generalization of the Weibull dis- tribution with application to the analysis of survival data. Journal of the American Statistical Association, 91, 1575-1583.

Pham, H. and Lai, CD. (2007). On recent generalizations of the Weibull distribution. IEEE transactions on reliability, 56, 454-458.

Shao, Q. X., Wong, H., Xia, J. and Ip, W. C. (2004). Models for extreme using the extended three-parameter Burr XII system with application to flood frequency analysis. Hydrol. Sci. J. 49, 685-702.

Weerahandi, S. and Johnson, R.A. (1992). Testing reliability in a stress-strength model when X and Y are normally distributed. Technometrics, 38, 83-91.

Xie, M. and Lai, C.D. (1995). Reliability analysis using an additive Weibull model with bathtub- shaped failure rate function. Reliability Engineering System Safety, 52, 87-93.



How to Cite

Ghosh, I., & Bourguinon, M. (2017). A New Extended Burr XII Distribution. Austrian Journal of Statistics, 46(1), 33-39. https://doi.org/10.17713/ajs.v46i1.139