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Likelihood-based inference for power distributions

机译:配电的基于似然性的推断

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摘要

This paper considers likelihood-based inference for the family of power distributions. Widely applicable results are presented which can be used to conduct inference for all three parameters of the general location-scale extension of the family. More specific results are given for the special case of the power normal model. The analysis of a large data set, formed from density measurements for a certain type of pollen, illustrates the application of the family and the results for likelihood-based inference. Throughout, comparisons are made with analogous results for the direct parametrisation of the skew-normal distribution.
机译:本文考虑了功率分布族的基于似然性的推断。提出了广泛适用的结果,可用于对家庭的一般位置范围扩展的所有三个参数进行推断。针对功率正态模型的特殊情况,给出了更具体的结果。对特定类型花粉的密度测量所形成的大型数据集的分析说明了该族的应用以及基于似然性推断的结果。贯穿整个过程,对偏正态分布的直接参数化进行了类似的比较。

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