A Weibull Generated Exponentiated Exponential Model: Properties and Bayes Interval Prediction

DOI

10.2991/jsta.2015.14.4.3How to use a DOI?

Keywords

Composed distributions; Weibull and exponentiated exponential distributions; one- and two-sample Bayes interval prediction; simulation.

Abstract

Motivated by the fact that the so-called Weibull generated exponentiated exponential distribution (WGEED) accommodates for non-monotone as well as monotone hazard rate functions (HRFs), we give some properties of this WGEED and explore its use in life testing by obtaining Bayes prediction intervals of future observables. The survival function (SF) of the WGEED is constructed by composing a Weibull cumulative distribution function (CDF) with –ln [exponentiated exponential] CDF. Some properties of the WGEED are given and prediction intervals of future observables, using the one- and two-sample schemes, are obtained. A comparison between the WGEE and the Weibull distributions, based on Kolmogorov-Smirnov goodness of fit test, shows that the former fits better than the latter. Real life data shows the possibility of using the WGEED in analyzing lifetime data. Numerical examples of one- and two- sample Bayes interval prediction are given to illustrate the procedure and a simulation study is made to compute the coverage probabilities and the average lengths of intervals.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - JOUR
AU  - Essam K. Al-Hussaini
AU  - Alaa H. Abdel-Hamid
PY  - 2015
DA  - 2015/12/01
TI  - A Weibull Generated Exponentiated Exponential Model: Properties and Bayes Interval Prediction
JO  - Journal of Statistical Theory and Applications
SP  - 368
EP  - 382
VL  - 14
IS  - 4
SN  - 2214-1766
UR  - https://doi.org/10.2991/jsta.2015.14.4.3
DO  - 10.2991/jsta.2015.14.4.3
ID  - Al-Hussaini2015
ER  -