WEIBULL BURR X DISTRIBUTION PROPERTIES AND APPLICATION | [Pakistan Journal of Statistics • 2017]

Author(s):

1. Noor A. Ibrahim: Department of Mathematics, Faculty of science, Universiti Putra Malaysia Selangor, Malaysia; Laboratory of Computational Statistics and Operations Research Institute for Mathematical Research, Universiti Putra Malaysia.

2. Mundher A. Khaleel: Department of Mathematics, Faculty of science, Universiti Putra Malaysia Selangor, Malaysia Department of Mathematics, Faculty of Computer Science and Mathematics University of Tikrit, Iraq

3. Faton Merovci: Faculty of Mechanical and Computer Engineering University of Mitrovica “Isa Boletini”, Kosovo

4. Adem Kilicman: Department of Mathematics, Faculty of science, Universiti Putra Malaysia Selangor, Malaysia.

5. Mahendran Shitan: Department of Mathematics, Faculty of science, Universiti Putra Malaysia Selangor, Malaysia; Laboratory of Computational Statistics and Operations Research Institute for Mathematical Research, Universiti Putra Malaysia.

Abstract:

In this paper, we developed a new continuous distribution called the Weibull-Burr type X distribution which extends the Burr type X distribution. We obtained expressions for the density and the cumulative function. We also derived various structural properties of the new distribution are included Quantile function, the moment, moment generating function, Renyi entropy and Order statistics. We estimate parameters by using Least Square, Weighted Least Square and Maximum Likelihood methods. additionally, the asymptotic confidence intervals for the parameters are derived from the Fisher information matrix. Finally, the obtained results are validated using a real data set and is shown that the new family provides a better fit than some other known distributions. This new distribution will serve as an alternative model to other models available in the literature for modelling positive real data in many areas.

Page(s): 315-336

DOI: DOI not available

Published: Journal: Pakistan Journal of Statistics, Volume: 33, Issue: 5, Year: 2017

Keywords:

estimation , quantile function , Order Statistics , Moment

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