Objective bayesian analysis of the Yule–Simon distribution with applications

Fabrizio Leisen*, Luca Rossini, Cristiano Villa

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

The Yule–Simon distribution is usually employed in the analysis of frequency data. As the Bayesian literature, so far, has ignored this distribution, here we show the derivation of two objective priors for the parameter of the Yule–Simon distribution. In particular, we discuss the Jeffreys prior and a loss-based prior, which has recently appeared in the literature. We illustrate the performance of the derived priors through a simulation study and the analysis of real datasets.

Original languageEnglish
Pages (from-to)99-126
Number of pages28
JournalComputational Statistics
Volume33
Issue number1
DOIs
Publication statusPublished - 1 Mar 2018
Externally publishedYes

Keywords

  • Kullback–Leibler divergence
  • Loss-based prior
  • Objective bayes
  • Social network daily returns
  • Text analysis

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