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原文連結
論文資訊
- 類型：已發表論文
- 日期：2009
摘要
Power-law distributions occur in many situations of scientific interest and have significant consequences for our understanding of natural and man-made phenomena. Unfortunately, the detection and characterization of 冪次定律s is complicated by the large fluctuations that occur in the tail of the distribution-the part of the distribution representing large but rare events-and by the difficulty of identifying the range over which power-law behavior holds. Commonly used methods for analyzing power-law data, such as least-squares fitting, can produce Substantially inaccurate estimates of parameters for power-law distributions, and even in cases where such methods return accurate answers they are still unsatisfactory because they give no indication of whether the data obey a 冪次定律 at all. Here we pr
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