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Applied Mathematical Modelling
Article
License: Elsevier Non-Commercial
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Applied Mathematical Modelling
Article . 2013
License: Elsevier Non-Commercial
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Applied Mathematical Modelling
Article . 2013 . Peer-reviewed
License: Elsevier Non-Commercial
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The generalized Gompertz distribution

Authors: Ahmad M. Alshamrani; Adel Naif Al-Otaibi; Awad El-Gohary;

The generalized Gompertz distribution

Abstract

AbstractThis paper deals with a new generalization of the exponential, Gompertz, and generalized exponential distributions. This distribution is called the generalized Gompertz distribution (GGD). The main advantage of this new distribution is that it has increasing or constant or decreasing or bathtub curve failure rate depending upon the shape parameter. This property makes GGD is very useful in survival analysis. Some statistical properties such as moments, mode, and quantiles are derived. The failure rate function is also derived. The maximum likelihood estimators of the parameters are derived using a simulations study. Real data set is used to determine whether the GGD is better than other well-known distributions in modeling lifetime data or not.

Related Organizations
Keywords

Gompertz distribution, Maximum likelihood estimators, Modelling and Simulation, Applied Mathematics, Generalized Gompertz distribution, Quantile, Mode and median

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
137
Top 1%
Top 1%
Top 10%
hybrid