A Versatile Distribution Based on the Incomplete Gamma Function: Characterization and Applications
In this study, we introduce a novel distribution related to the gamma distribution, referred to as the generalized incomplete gamma distribution. This new family is defined through a stochastic representation involving a linear transformation of a random variable following a distribution derived fro...
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MDPI AG
2025-05-01
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| Series: | Mathematics |
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| author | Jimmy Reyes Carolina Marchant Karol I. Santoro Yuri A. Iriarte |
| author_facet | Jimmy Reyes Carolina Marchant Karol I. Santoro Yuri A. Iriarte |
| author_sort | Jimmy Reyes |
| collection | DOAJ |
| description | In this study, we introduce a novel distribution related to the gamma distribution, referred to as the generalized incomplete gamma distribution. This new family is defined through a stochastic representation involving a linear transformation of a random variable following a distribution derived from the upper incomplete gamma function. As a result, the proposed distribution exhibits a probability density function that effectively captures data exhibiting asymmetry and both mild and high levels of kurtosis, providing greater flexibility compared to the conventional gamma distribution. We analyze the probability density function and explore fundamental properties, including moments, skewness, and kurtosis coefficients. Parameter estimation is conducted via the maximum likelihood method, and a Monte Carlo simulation study is performed to assess the asymptotic properties of the maximum likelihood estimators. To illustrate the applicability of the proposed distribution, we present two case studies involving real-world datasets related to mineral concentration and the length of odontoblasts in guinea pigs, demonstrating that the proposed distribution provides a superior fit compared to the gamma, inverse Gaussian, and slash-type distributions. |
| format | Article |
| id | doaj-art-ff97cfd2d4144d0280d44790448f7644 |
| institution | OA Journals |
| issn | 2227-7390 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj-art-ff97cfd2d4144d0280d44790448f76442025-08-20T02:32:55ZengMDPI AGMathematics2227-73902025-05-011311174910.3390/math13111749A Versatile Distribution Based on the Incomplete Gamma Function: Characterization and ApplicationsJimmy Reyes0Carolina Marchant1Karol I. Santoro2Yuri A. Iriarte3Departamento de Estadística y Ciencia de Datos, Facultad de Ciencias Básicas, Universidad de Antofagasta, Antofagasta 1240000, ChileFaculty of Basic Sciences, Universidad Católica del Maule, Talca 3480112, ChileDepartamento de Estadística y Ciencia de Datos, Facultad de Ciencias Básicas, Universidad de Antofagasta, Antofagasta 1240000, ChileDepartamento de Estadística y Ciencia de Datos, Facultad de Ciencias Básicas, Universidad de Antofagasta, Antofagasta 1240000, ChileIn this study, we introduce a novel distribution related to the gamma distribution, referred to as the generalized incomplete gamma distribution. This new family is defined through a stochastic representation involving a linear transformation of a random variable following a distribution derived from the upper incomplete gamma function. As a result, the proposed distribution exhibits a probability density function that effectively captures data exhibiting asymmetry and both mild and high levels of kurtosis, providing greater flexibility compared to the conventional gamma distribution. We analyze the probability density function and explore fundamental properties, including moments, skewness, and kurtosis coefficients. Parameter estimation is conducted via the maximum likelihood method, and a Monte Carlo simulation study is performed to assess the asymptotic properties of the maximum likelihood estimators. To illustrate the applicability of the proposed distribution, we present two case studies involving real-world datasets related to mineral concentration and the length of odontoblasts in guinea pigs, demonstrating that the proposed distribution provides a superior fit compared to the gamma, inverse Gaussian, and slash-type distributions.https://www.mdpi.com/2227-7390/13/11/1749gamma distributionincomplete gamma functionkurtosismaximum likelihoodmomentsskewness |
| spellingShingle | Jimmy Reyes Carolina Marchant Karol I. Santoro Yuri A. Iriarte A Versatile Distribution Based on the Incomplete Gamma Function: Characterization and Applications Mathematics gamma distribution incomplete gamma function kurtosis maximum likelihood moments skewness |
| title | A Versatile Distribution Based on the Incomplete Gamma Function: Characterization and Applications |
| title_full | A Versatile Distribution Based on the Incomplete Gamma Function: Characterization and Applications |
| title_fullStr | A Versatile Distribution Based on the Incomplete Gamma Function: Characterization and Applications |
| title_full_unstemmed | A Versatile Distribution Based on the Incomplete Gamma Function: Characterization and Applications |
| title_short | A Versatile Distribution Based on the Incomplete Gamma Function: Characterization and Applications |
| title_sort | versatile distribution based on the incomplete gamma function characterization and applications |
| topic | gamma distribution incomplete gamma function kurtosis maximum likelihood moments skewness |
| url | https://www.mdpi.com/2227-7390/13/11/1749 |
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