Objective & Hypothesis:Although Akaike information criterion is the most popular selection criterion in the literature, it gives inconsistent results in determining the correct model according to other selection criteria in transmuted distribution families.
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Key Findings & Data:A Monte Carlo simulation study is considered to compare the performances of this new criterion with the Akaike information criterion.
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Conclusion & Impact:Also, a numerical example is presented.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Akaike information criterion · Modified Akaike information criterion · Monte Carlo simulation
Abstract
Although Akaike information criterion is the most popular selection criterion in the literature, it gives inconsistent results in determining the correct model according to other selection criteria in transmuted distribution families. We motivate a new extension of the Akaike information criterion in the solution of this problem. In this paper, we suggest a new selection criterion as an alternative to the Akaike information criterion for the family of transmuted distribution. We discuss special cases of this family based on exponential distribution. A Monte Carlo simulation study is considered to compare the performances of this new criterion with the Akaike information criterion. Also, a numerical example is presented.
Tanış, C., Akdoğan, Y., Karakaya, K., Özkan, E. (2021). A NEW ALTERNATIVE SELECTION CRITERION FOR FAMILY OF SOME TRANSMUTED DISTRIBUTIONS BASED ON EXPONENTIAL DISTRIBUTION. Mugla Journal of Science and Technology, Volume: 7 Issue: 1. https://doi.org/10.22531/muglajsci.816089
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