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Parameter and quantile estimation for the three-parameter gamma distribution based on statistics invariant to unknown location

机译:基于未知位置不变的统计量的三参数伽马分布的参数和分位数估计

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摘要

The three-parameter gamma distribution is widely used as a model for distributions of life spans, reaction times, and for other types of skewed data. In this paper, we propose an efficient method of estimation for the parameters and quantiles of the three-parameter gamma distribution, which avoids the problem of unbounded likelihood, based on statistics invariant to unknown location. Through a Monte Carlo simulation study, we then show that the proposed method performs well compared to other prominent methods in terms of bias and mean squared error. Finally, we present two illustrative examples.
机译:三参数伽马分布被广泛用作寿命,反应时间和其他类型的偏斜数据分布的模型。在本文中,我们提出了一种有效的方法来估计三参数伽马分布的参数和分位数,从而避免了基于未知位置不变的统计数据的无界似然性问题。通过蒙特卡洛模拟研究,我们然后证明了在偏倚和均方误差方面,所提出的方法与其他主要方法相比表现良好。最后,我们给出两个说明性的例子。

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