Objective bayesian analysis of the Yule–Simon distribution with applicationsReport as inadecuate




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Computational Statistics

pp 1–28

First Online: 05 June 2017Received: 14 August 2016Accepted: 13 May 2017DOI: 10.1007-s00180-017-0735-1

Cite this article as: Leisen, F., Rossini, L. & Villa, C. Comput Stat 2017. doi:10.1007-s00180-017-0735-1

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.

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



Author: Fabrizio Leisen - Luca Rossini - Cristiano Villa

Source: https://link.springer.com/







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