Abstract
The extended three-parameter Burr XII (EBXII) distribution has recently attracted considerable attention for modeling data from various scientific fields since it yields a wide range of skewness and kurtosis values. However, it is well known that the parameter estimates have significant effects on the success of a distribution in real-life applications. In this study, modified moment estimators (MMEs) and modified probability-weighted moments estimators (MPWMEs) are used to estimate the parameters of the EBXII distribution. These two considered estimators are also compared with the commonly used maximum-likelihood, percentiles, least-squares and weighted least-squares estimators in terms of bias and efficiency via an extensive numerical simulation. The MMEs and MPWMEs are observed to perform well in varying sample cases, and the simulation results are supported with application through a real-life data set.
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