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August 27, 2024Fluctuation and Noise Letters9 citations

Fisher-based inaccuracy information measure

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OKOmid KharazmiJCJavier E. Contreras‐ReyesNBN. Balakrishnan

Key Points

  • The proposed Fisher-based inaccuracy information (FBII) measure offers an innovative way to quantify information.
  • In optimization scenarios, the harmonic-mixture distribution maximizes information as determined by the Bayes-Fisher-based inaccuracy information (BFBII) measure.
  • Analysis reveals connections between the BFBII measure and both Kullback-Leibler and chi-square divergence measures, enhancing theoretical understanding of information metrics. Our findings illustrate the FBII measure's application across various distribution types, including skew-normal and Student-t forms.

Abstract

We introduce a new inaccuracy measure in terms of Fisher information. The proposed information measure is referred to as Fisher-based inaccuracy information (FBII) measure. Next, we examine some properties of this information measure and specifically examine it for escort and equilibrium distributions. Further, we propose Bayes–Fisher-based inaccuracy information (BFBII) measure and examine its connection to Kullback–Leibler and chi-square divergence measures. Moreover, in three different optimization problems, we show that the harmonic-mixture distribution gives optimal information based on BFBII measure. Some examples of FBII measure and escort density related to skew-normal and Student-t distributions are also illustrated, and then are applied to fish condition factor time series.

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Cite This Study

Kharazmi et al. (2024) studied this question.

synapsesocial.com/papers/68e5aa67b6db643587544d3fhttps://doi.org/10.1142/s0219477525500099
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