重尾分布（Heavy-tailed distribution）是一种概率分布模型，它的尾部比指数分布还要厚。在许多情况下，右边尾部的部分比较受到重视，但左边尾部比较厚，或是两边尾部都比较厚的状况，也被认为是一种重尾分布。
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已发现一类着色问题的求解，显现出重尾分布的现象。
We observe the heavy-tailed distribution of cycles in solving some graph coloring instances.
正规变化重尾分布的尾部指数的估计方法有很多种，但都不同程度地存在一定的局限性。
The estimation of tail index for regular variation heavy-tailed distributions aroused our concern, many scholars proposed several methods, but all of them have some disadvantages.
本文分析了流量动态特性产生的不平衡性及其重尾分布，提出了基于重尾分布的流量分类定量分析模型。
By analyzing the imbalance and heavy-tailed distribution of Internet traffic, a heavy-tailed traffic based classification model for quantitative analysis is proposed.
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