Jensen-Fisher and Jensen-χ2 information measures for finite mixture distributions

Document Type : Original Paper


1 Department of Statistics, Faculty of Mathematical Sciences, Vali-e-Asr University of Rafsanjan, Iran

2 Department of Statistics, Faculty of Intelligent Systems Engineering and Data Science, Persian Gulf University, Bushehr, Iran


In this paper, first, considering Fisher information of parametric type, we introduce a new information

measure based on Jensen inequality. Then, the Fisher information matrix and Jensen-Fisher are studied

or a finite mixture distribution of probability density functions. Further, another information criterion is

introduced as Jensen-χ2 based on a mixture of probability density functions. Generalizations of Jensen-Fisher and Jensen-χ2 information measures are presented based on m probability density functions and the relationship between these two new information criteria as well as the relationship between Jensen-Fisher information and some known information criteria such as Jensen-Shannon and Jeffreys information

measures are studied.


Main Subjects

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Volume 11, Issue 4 - Serial Number 4
December 2021
Pages 699-711
  • Receive Date: 13 August 2021
  • Revise Date: 15 November 2021
  • Accept Date: 25 November 2021
  • First Publish Date: 05 December 2021