本福德或不本福德：一个系统的，但并不总是有根据的使用一个优雅的法律在实验领域
Benford or not Benford: a systematic but not always well-founded use of an elegant law in experimental fields
摘要：
在本文中，我们将看到，数据中d作为前导数字d $\in$ 1，9的比例（通过以下开发的模型获得）更可能遵循其概率分布由特定上界确定的定律，而不是本福德定律。这些概率分布在本福德值附近波动，正如在许多自然发生的数据集合中的文献中经常可以观察到的那样（其中考虑的物理，生物或经济量是上限）。事先知道上界的值可以找到比本福德定律更好的调整定律。
英文摘要：
In this paper, we will see that the proportion of d as leading digit, d $\in$ 1, 9, in data (obtained thanks to the hereunder developed model) is more likely to follow a law whose probability distribution is determined by a specific upper bound, rather than Benford's Law. These probability distributions fluctuate around Benford's value as can often be observed in the literature in many naturally occurring collections of data (where the physical , biological or economical quantities considered are upper bounded). Knowing beforehand the value of the upper bound can be a way to find a better adjusted law than Benford's one.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
