Journal of Statistical Theory and Applications

Volume 16, Issue 2, June 2017, Pages 248 - 260

Bayesian Estimation of the Kumaraswamy Inverse Weibull Distribution

Authors
Felipe R.S. de Gusmão, Vera L.D. Tomazella, Ricardo S. Ehlers
Corresponding Author
Felipe R.S. de Gusmão
Received 25 September 2015, Accepted 23 August 2016, Available Online 1 June 2017.
DOI
https://doi.org/10.2991/jsta.2017.16.2.9How to use a DOI?
Keywords
Kumaraswamy distribution; Weibull distribution; Survival; Bayesian analysis.
Abstract

The Kumaraswamy InverseWeibull distribution has the ability to model failure rates that have unimodal shapes and are quite common in reliability and biological studies. The three-parameter Kumaraswamy InverseWeibull distribution with decreasing and unimodal failure rate is introduced. We provide a comprehensive treatment of the mathematical properties of the Kumaraswany Inverse Weibull distribution and derive expressions for its moment generating function and the r-th generalized moment. Some properties of the model with some graphs of density and hazard function are discussed. We also discuss a Bayesian approach for this distribution and an application was made for a real data set.

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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Journal
Journal of Statistical Theory and Applications
Volume-Issue
16 - 2
Pages
248 - 260
Publication Date
2017/06/01
ISSN (Online)
2214-1766
ISSN (Print)
1538-7887
DOI
https://doi.org/10.2991/jsta.2017.16.2.9How to use a DOI?
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/).

Cite this article

TY  - JOUR
AU  - Felipe R.S. de Gusmão
AU  - Vera L.D. Tomazella
AU  - Ricardo S. Ehlers
PY  - 2017
DA  - 2017/06/01
TI  - Bayesian Estimation of the Kumaraswamy Inverse Weibull Distribution
JO  - Journal of Statistical Theory and Applications
SP  - 248
EP  - 260
VL  - 16
IS  - 2
SN  - 2214-1766
UR  - https://doi.org/10.2991/jsta.2017.16.2.9
DO  - https://doi.org/10.2991/jsta.2017.16.2.9
ID  - deGusmão2017
ER  -