Bernoulli Poisson Moment Exponential Distribution: Mathematical Properties, Regression Model, and Applications

We introduce a new flexible count distribution by combining Bernoulli and Poisson moment exponential (PMEx) distributions. The new model named the Bernoulli PMEx distribution. Some mathematical properties are studied, including the hazard rate function, moments, moment generating function, probabili...

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Main Author: Amani Alrumayh
Format: Article
Language:English
Published: Wiley 2024-01-01
Series:International Journal of Mathematics and Mathematical Sciences
Online Access:http://dx.doi.org/10.1155/2024/5687958
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author Amani Alrumayh
author_facet Amani Alrumayh
author_sort Amani Alrumayh
collection DOAJ
description We introduce a new flexible count distribution by combining Bernoulli and Poisson moment exponential (PMEx) distributions. The new model named the Bernoulli PMEx distribution. Some mathematical properties are studied, including the hazard rate function, moments, moment generating function, probability generating function, and dispersion index. A count regression model is also proposed based on this distribution. The maximum likelihood estimation method is used to estimate the model parameters. In the end, three datasets from different fields are utilized for application purposes. The findings show that the new model efficiently analyzed these datasets as compared to Poisson, discrete Pareto, discrete Rayleigh, discrete Burr-Hatke, and discrete inverted Topp–Leone distributions.
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institution Kabale University
issn 1687-0425
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publishDate 2024-01-01
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series International Journal of Mathematics and Mathematical Sciences
spelling doaj-art-5f63f53082ed43e39487a945c5e1acd82025-02-03T05:29:50ZengWileyInternational Journal of Mathematics and Mathematical Sciences1687-04252024-01-01202410.1155/2024/5687958Bernoulli Poisson Moment Exponential Distribution: Mathematical Properties, Regression Model, and ApplicationsAmani Alrumayh0Department of MathematicsWe introduce a new flexible count distribution by combining Bernoulli and Poisson moment exponential (PMEx) distributions. The new model named the Bernoulli PMEx distribution. Some mathematical properties are studied, including the hazard rate function, moments, moment generating function, probability generating function, and dispersion index. A count regression model is also proposed based on this distribution. The maximum likelihood estimation method is used to estimate the model parameters. In the end, three datasets from different fields are utilized for application purposes. The findings show that the new model efficiently analyzed these datasets as compared to Poisson, discrete Pareto, discrete Rayleigh, discrete Burr-Hatke, and discrete inverted Topp–Leone distributions.http://dx.doi.org/10.1155/2024/5687958
spellingShingle Amani Alrumayh
Bernoulli Poisson Moment Exponential Distribution: Mathematical Properties, Regression Model, and Applications
International Journal of Mathematics and Mathematical Sciences
title Bernoulli Poisson Moment Exponential Distribution: Mathematical Properties, Regression Model, and Applications
title_full Bernoulli Poisson Moment Exponential Distribution: Mathematical Properties, Regression Model, and Applications
title_fullStr Bernoulli Poisson Moment Exponential Distribution: Mathematical Properties, Regression Model, and Applications
title_full_unstemmed Bernoulli Poisson Moment Exponential Distribution: Mathematical Properties, Regression Model, and Applications
title_short Bernoulli Poisson Moment Exponential Distribution: Mathematical Properties, Regression Model, and Applications
title_sort bernoulli poisson moment exponential distribution mathematical properties regression model and applications
url http://dx.doi.org/10.1155/2024/5687958
work_keys_str_mv AT amanialrumayh bernoullipoissonmomentexponentialdistributionmathematicalpropertiesregressionmodelandapplications