样本无数可调参数对s - α - s分布特征的适应

V. Lukin, A. Roenko, S. Abramov, I. Djurović
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引用次数: 8

摘要

服从重尾对称稳定(SalphaS)分布的过程已被证明可以很好地描述无线电工程、声学、通信等领域的许多自然现象。为了处理这类数据,需要应用稳健估计器,基于样本无数的方法被认为是准最优方法。样本无数估计需要设置一个可调的参数k。然而,关于它的选择只有非常近似和不切实际的建议。因此,在本文中,我们考虑了在实际应用中处理设k的一些方法。结果表明,该方法对数据样本规模和尾重都有较好的适应性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Adaptation of sample myriad tunable parameter to characteristics of SαS distribution
Processes obeying heavy-tailed symmetric alpha-stable (SalphaS) distributions have been shown to describe well many natural phenomena in radio engineering, acoustics, communications, etc. For processing such data, one needs to apply robust estimators and the methods based on a sample myriad are considered quasi-optimal ones. Sample myriad estimation requires setting a tunable parameter k. However, only quite approximate and impractical recommendations concerning its selection exist. Thus, in this paper we consider some approaches to deal with setting k in practical applications. It is shown that they are to be adaptive to data sample scale and tail heaviness.
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