Corpus ID: 118393218

Resolving Histogram Binning Dilemmas with Binless and Binfull Algorithms

  title={Resolving Histogram Binning Dilemmas with Binless and Binfull Algorithms},
  author={Abram Krislock and Nathan Krislock},
  journal={arXiv: Data Analysis, Statistics and Probability},
  • Abram Krislock, Nathan Krislock
  • Published 2014
  • Physics, Computer Science
  • arXiv: Data Analysis, Statistics and Probability
  • The histogram is an analysis tool in widespread use within many sciences, with high energy physics as a prime example. However, there exists an inherent bias in the choice of binning for the histogram, with dierent choices potentially leading to dierent interpretations. This paper aims to eliminate this bias using two \debinning" algorithms. Both algorithms generate an observed cumulative distribution function from the data, and use it to construct a representation of the underlying probability… CONTINUE READING

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