<Previous Article In Issue
Volume 17, Issue 4, December 2018, Pages 719 - 727
Weibull-Normal Distribution and its Applications
Authors
Felix Famoye1, *, Eno Akarawak2, Matthew Ekum3
1Department of Mathematics, Central Michigan University, Mt. Pleasant, Michigan, USA
2Department of Mathematics, University of Lagos, Akoka-Yaba, Lagos, Nigeria
3Department of Mathematics & Statistics, Lagos State Polytechnic, Ikorodu, Lagos, Nigeria
*
Corresponding author. Email: felix.famoye@cmich.edu
Received 2 March 2016, Accepted 19 July 2017, Available Online 31 December 2018.
- DOI
- 10.2991/jsta.2018.17.4.12How to use a DOI?
- Keywords
- T-R{Y} framework; Bimodal; Hazard function; Estimation
- Abstract
In this paper, a Weibull-normal distribution, based on the standard quantile function of log-logistic distribution, is defined and studied. Some properties of the probability distribution are discussed. The Weibull-normal distribution is found to be unimodal or bimodal. The distribution can be right skewed or left skewed. The method of maximum likelihood estimation is suggested to estimate the parameters of the distribution. Three numerical data sets are used to illustrate the applications of the Weibull-normal distribution.
- Copyright
- © 2018 The Authors. Published by Atlantis Press SARL.
- Open Access
- This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).
Download article (PDF)
View full text (HTML)
<Previous Article In Issue
Cite this article
TY - JOUR AU - Felix Famoye AU - Eno Akarawak AU - Matthew Ekum PY - 2018 DA - 2018/12/31 TI - Weibull-Normal Distribution and its Applications JO - Journal of Statistical Theory and Applications SP - 719 EP - 727 VL - 17 IS - 4 SN - 2214-1766 UR - https://doi.org/10.2991/jsta.2018.17.4.12 DO - 10.2991/jsta.2018.17.4.12 ID - Famoye2018 ER -