International Journal of Mathematics Trends and Technology
Volume 68 | Issue 8 | Year 2022 | Article Id. IJMTT-V68I8P508 | DOI : https://doi.org/10.14445/22315373/IJMTT-V68I8P508
| Received | Revised | Accepted | Published |
|---|---|---|---|
| 01 Jul 2022 | 02 Aug 2022 | 15 Aug 2022 | 26 Aug 2022 |
This paper proposes a four-parameterized distribution, namely an extended Kumaraswamy-Gull Alpha Power Exponential distribution. The proposed distribution gives rise to some well-known sub-models. Some basic properties of the distribution are derived. The method of maximum likelihood estimation was employed to estimate the parameters of the distribution. A Monte Carlo simulation study was conducted to evaluate the performance of the MLE estimates. From the simulation results, it is observed that with an increase in sample size the average estimates approach the true value of the parameters, and the average bias, MSE, and RMSE decrease, in general. The proposed K-GAPE distribution is fitted to two real data sets and compared to its sub-models. A conclusion can be made that the purposed distribution performs better than its underlying sub-models.
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Mohamed Kpangay, Leo O. Odongo, George O. Orwa, "An Extended Kumaraswamy-Gull Alpha Power Exponential Distribution: Properties and Application to Real Data," International Journal of Mathematics Trends and Technology (IJMTT), vol. 68, no. 8, pp. 72-104, 2022. Crossref, https://doi.org/10.14445/22315373/IJMTT-V68I8P508
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