PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
August 5, 2021Mathematics49 citationsOpen Access

Theory and Applications of the Unit Gamma/Gompertz Distribution

RBRashad A. R. BantanFJFarrukh JamalCCChristophe Chesneau

Key Points

Key points are not available for this paper at this time.

Abstract

Unit distributions are commonly used in probability and statistics to describe useful quantities with values between 0 and 1, such as proportions, probabilities, and percentages. Some unit distributions are defined in a natural analytical manner, and the others are derived through the transformation of an existing distribution defined in a greater domain. In this article, we introduce the unit gamma/Gompertz distribution, founded on the inverse-exponential scheme and the gamma/Gompertz distribution. The gamma/Gompertz distribution is known to be a very flexible three-parameter lifetime distribution, and we aim to transpose this flexibility to the unit interval. First, we check this aspect with the analytical behavior of the primary functions. It is shown that the probability density function can be increasing, decreasing, “increasing-decreasing” and “decreasing-increasing”, with pliant asymmetric properties. On the other hand, the hazard rate function has monotonically increasing, decreasing, or constant shapes. We complete the theoretical part with some propositions on stochastic ordering, moments, quantiles, and the reliability coefficient. Practically, to estimate the model parameters from unit data, the maximum likelihood method is used. We present some simulation results to evaluate this method. Two applications using real data sets, one on trade shares and the other on flood levels, demonstrate the importance of the new model when compared to other unit models.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Bantan et al. (2021) studied this question.

synapsesocial.com/papers/6a1bc39fea84844e355ee9d6https://doi.org/10.3390/math9161850
Ask AI
Helpful
Bookmark
Share
View Full Paper