不对称均匀拉普拉斯分布:性质与应用

IF 0.1 Q4 STATISTICS & PROBABILITY
Fatemeh Arezoomand, M. Yarmohammadi, R. Mahmoudvand
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引用次数: 0

摘要

本研究的目的是引入一种非对称均匀拉普拉斯分布。我们对这种分布进行了详细的理论描述。我们尝试使用最大似然法来估计AUL分布的参数。由于似然方法会产生复杂的形式,我们建议使用一种基于自举的方法来估计参数。所提出的方法主要是基于经验密度的形状。我们进行了一项模拟研究,以评估所提出程序的性能。我们还将AUL分布拟合到真实数据集:每日工作时间和Pontius数据集。结果表明,AUL分布比斜正态分布、斜t分布、非对称拉普拉斯分布和均匀正态分布更合适。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Asymmetric Uniform-Laplace distribution: Properties and Applications
The goal of this study is to introduce an Asymmetric Uniform-Laplace (AUL) distribution. We present a detailed theoretical description of this distribution. We try to estimate the parameters of AUL distribution using the maximum likelihood method. Since the likelihood approach results in complicated forms, we suggest a bootstrapbased approach for estimating the parameters. The proposed method is mainly based on the shape of the empirical density. We conduct a simulation study to assess the performance of the proposed procedure. We also fit the AUL distribution to real data sets: daily working time and Pontius data sets. The results show that AUL distribution is a more appropriate choice than the Skew-Normal, Skew t, Asymmetric Laplace and Uniform-Normal distributions.
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CiteScore
1.50
自引率
0.00%
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