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Estimator based on percentiles for log-logistic distribution

机译:基于百分比的日志逻辑分发百分比

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In this study, we consider the estimator based on percentiles for log-logistic distribution similar to the study of [6] and we also graph breakdown plots of the estimators that are considered below to have an opinion about robustness properties. The estimator based on percentiles is explicit functions of sample percentiles, thus, easy to compute and do not involve any iterative computational complexities like Maximum likelihood estimator (MLE). The simulation results show that the considered estimator performs better than MLE for small sample sizes.
机译:在本研究中,我们考虑基于百分比的估算员,与[6]的研究类似的日志逻辑分布,我们还在下面考虑的估计器的击穿图来对鲁棒性属性进行意见。基于百分位数的估计器是示例百分比的明确功能,因此易于计算,并且不涉及与最大似然估计器(MLE)相同的任何迭代计算复杂性。仿真结果表明,所考虑的估计器比MLE更好地表现出小型样本尺寸。

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