Artikel

A study on exponentiated Gompertz distribution under Bayesian discipline using informative priors

The exponentiated Gompertz (EGZ) distribution has been recently used in almost all areas of human endeavours, starting from modelling lifetime data to cancer treatment. Various applications and properties of the EGZ distribution are provided by Anis and De (2020). This paper explores the important properties of the EGZ distribution under Bayesian discipline using two informative priors: the Gamma Prior (GP) and the Inverse Levy Prior (ILP). This is done in the framework of five selected loss functions. The findings show that the two best loss functions are the Weighted Balance Loss Function (WBLF) and the Quadratic Loss Function (QLF). The usefulness of the model is illustrated by the use of real life data in relation to simulated data. The empirical results of the comparison are presented through a graphical illustration of the posterior distributions.

Sprache
Englisch

Erschienen in
Journal: Statistics in Transition New Series ; ISSN: 2450-0291 ; Volume: 22 ; Year: 2021 ; Issue: 4 ; Pages: 101-119 ; New York: Exeley

Thema
exponentiated Gompertz distribution
loss functions
informative priors
Bayes estimators
posterior risks

Ereignis
Geistige Schöpfung
(wer)
Aslam, Muhammad
Afzaal, Mehreen
Bhatti, Muhammad Ishaq
Ereignis
Veröffentlichung
(wer)
Exeley
(wo)
New York
(wann)
2021

DOI
doi:10.21307/stattrans-2021-040
Handle
Letzte Aktualisierung
10.03.2025, 11:42 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Artikel

Beteiligte

  • Aslam, Muhammad
  • Afzaal, Mehreen
  • Bhatti, Muhammad Ishaq
  • Exeley

Entstanden

  • 2021

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