Zipf's Law and the Frequency of Characters or Words of Oracles
This work addresses the statistical modeling of ancient text data for linguists and historians, but it appears incremental as it applies existing laws to a specific dataset.
The authors analyzed the frequency distribution of characters or words in Oracle texts, finding that it follows Zipf-Mandelbrot or three-parameter Zipf's law, and they estimated the parameters based on the data, while critiquing prior claims about data patterns as impressionistic.
The article discusses the frequency of characters of Oracle,concluding that the frequency and the rank of a word or character is fit to Zipf-Mandelboit Law or Zipf's law with three parameters,and figuring out the parameters based on the frequency,and pointing out that what some researchers of Oracle call the assembling on the two ends is just a description by their impression about the Oracle data.