An Exponentiated Inverse Exponential Distribution Properties and Applications
This paper introduces Exponentiated Inverse Exponential Distribution (EIED), a novel probability model developed within the power inverse exponential distribution framework. A distinctive feature of EIED is its highly flexible hazard rate function, which can exhibit increasing, decreasing, and rever...
| Published in: | Axioms |
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| Main Authors: | , , , , |
| Format: | Article |
| Language: | English |
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MDPI AG
2025-10-01
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| Online Access: | https://www.mdpi.com/2075-1680/14/10/753 |
| _version_ | 1848668740454973440 |
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| author | Aroosa Mushtaq Tassaddaq Hussain Mohammad Shakil Mohammad Ahsanullah Bhuiyan Mohammad Golam Kibria |
| author_facet | Aroosa Mushtaq Tassaddaq Hussain Mohammad Shakil Mohammad Ahsanullah Bhuiyan Mohammad Golam Kibria |
| author_sort | Aroosa Mushtaq |
| collection | DOAJ |
| container_title | Axioms |
| description | This paper introduces Exponentiated Inverse Exponential Distribution (EIED), a novel probability model developed within the power inverse exponential distribution framework. A distinctive feature of EIED is its highly flexible hazard rate function, which can exhibit increasing, decreasing, and reverse bathtub (upside-down bathtub) shapes, making it suitable for modeling diverse lifetime phenomena in reliability engineering, survival analysis, and risk assessment. We derived comprehensive statistical properties of the distribution, including the reliability and hazard functions, moments, characteristic and quantile functions, moment generating function, mean deviations, Lorenz and Bonferroni curves, and various entropy measures. The identifiability of the model parameters was rigorously established, and maximum likelihood estimation was employed for parameter inference. Through extensive simulation studies, we demonstrate the robustness of the estimation procedure across different parameter configurations. The practical utility of EIED was validated through applications to real-world datasets, where it showed superior performance compared to existing distributions. The proposed model offers enhanced flexibility for modeling complex lifetime data with varying hazard patterns, particularly in scenarios involving early failure periods, wear-in phases, and wear-out behaviors. |
| format | Article |
| id | doaj-art-e07907f971134835b305d08cd833fe78 |
| institution | Directory of Open Access Journals |
| issn | 2075-1680 |
| language | English |
| publishDate | 2025-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| spelling | doaj-art-e07907f971134835b305d08cd833fe782025-10-28T16:31:09ZengMDPI AGAxioms2075-16802025-10-01141075310.3390/axioms14100753An Exponentiated Inverse Exponential Distribution Properties and ApplicationsAroosa Mushtaq0Tassaddaq Hussain1Mohammad Shakil2Mohammad Ahsanullah3Bhuiyan Mohammad Golam Kibria4Department of Mathematics, Kings College, Mirpur 10250, PakistanDepartment of Statistics, Mirpur University of Science and Technology, Mirpur 10250, PakistanDepartment of Mathematics, Miami Dade College, Hialeah, FL 33012, USADepartment of Management Sciences, Rider University, Lawrenceville, NJ 08648, USADepartment of Mathematics & Statistics, Florida International University, Miami, FL 33199, USAThis paper introduces Exponentiated Inverse Exponential Distribution (EIED), a novel probability model developed within the power inverse exponential distribution framework. A distinctive feature of EIED is its highly flexible hazard rate function, which can exhibit increasing, decreasing, and reverse bathtub (upside-down bathtub) shapes, making it suitable for modeling diverse lifetime phenomena in reliability engineering, survival analysis, and risk assessment. We derived comprehensive statistical properties of the distribution, including the reliability and hazard functions, moments, characteristic and quantile functions, moment generating function, mean deviations, Lorenz and Bonferroni curves, and various entropy measures. The identifiability of the model parameters was rigorously established, and maximum likelihood estimation was employed for parameter inference. Through extensive simulation studies, we demonstrate the robustness of the estimation procedure across different parameter configurations. The practical utility of EIED was validated through applications to real-world datasets, where it showed superior performance compared to existing distributions. The proposed model offers enhanced flexibility for modeling complex lifetime data with varying hazard patterns, particularly in scenarios involving early failure periods, wear-in phases, and wear-out behaviors.https://www.mdpi.com/2075-1680/14/10/753DUS-power transformationestimationgoodness of fit testhazard rate functionstatistical distribution |
| spellingShingle | Aroosa Mushtaq Tassaddaq Hussain Mohammad Shakil Mohammad Ahsanullah Bhuiyan Mohammad Golam Kibria An Exponentiated Inverse Exponential Distribution Properties and Applications DUS-power transformation estimation goodness of fit test hazard rate function statistical distribution |
| title | An Exponentiated Inverse Exponential Distribution Properties and Applications |
| title_full | An Exponentiated Inverse Exponential Distribution Properties and Applications |
| title_fullStr | An Exponentiated Inverse Exponential Distribution Properties and Applications |
| title_full_unstemmed | An Exponentiated Inverse Exponential Distribution Properties and Applications |
| title_short | An Exponentiated Inverse Exponential Distribution Properties and Applications |
| title_sort | exponentiated inverse exponential distribution properties and applications |
| topic | DUS-power transformation estimation goodness of fit test hazard rate function statistical distribution |
| url | https://www.mdpi.com/2075-1680/14/10/753 |
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