Comparative evaluation shows that maximum likelihood estimation accurately estimates parameters in inverse Weibull distribution, indicating practical implications for data analysis.
This paper presents a comparative evaluation of three distinct methodologies for estimating the parameters of the Inverse Weibull distribution under Type-I right censoring: trimmed linear moments (using Type-AT and Type-BT variants), direct linear moments (using Type-AD and Type-BD variants), and maximum likelihood estimation. The performance of these methods is assessed through Monte Carlo simulations, focusing on estimation accuracy, relative absolute bias, and root mean square error to identify the most appropriate approach. The practical applicability of these techniques is demonstrated through a real-world dataset analysis.
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Ibrahim et al. (2025) studied this question.
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