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Characterizations of Bivariate Models Using Some Dynamic Conditional Information Divergence Measures

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  • J. Navarro
  • S. M. Sunoj
  • M. N. Linu

Abstract

In this article, we study some relevant information divergence measures viz. Renyi divergence and Kerridge’s inaccuracy measures. These measures are extended to conditionally specified models and they are used to characterize some bivariate distributions using the concepts of weighted and proportional hazard rate models. Moreover, some bounds are obtained for these measures using the likelihood ratio order.

Suggested Citation

  • J. Navarro & S. M. Sunoj & M. N. Linu, 2014. "Characterizations of Bivariate Models Using Some Dynamic Conditional Information Divergence Measures," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 43(9), pages 1939-1948, May.
    • Handle: RePEc:taf:lstaxx:v:43:y:2014:i:9:p:1939-1948
    DOI: 10.1080/03610926.2012.677925
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    Cited by:

    1. Nair Rohini S. & Abdul Sathar E. I., 2019. "Bivariate Dynamic Weighted Survival Entropy of Order 𝛼," Stochastics and Quality Control, De Gruyter, vol. 34(2), pages 67-85, December.
    2. Amit Ghosh & Chanchal Kundu, 2018. "Chernoff distance for conditionally specified models," Statistical Papers, Springer, vol. 59(3), pages 1061-1083, September.
    3. Amit Ghosh & Chanchal Kundu, 2019. "Bivariate extension of (dynamic) cumulative residual and past inaccuracy measures," Statistical Papers, Springer, vol. 60(6), pages 2225-2252, December.
    4. Park, Sangun & Pakyari, Reza, 2015. "Cumulative residual Kullback–Leibler information with the progressively Type-II censored data," Statistics & Probability Letters, Elsevier, vol. 106(C), pages 287-294.
    5. Rajesh, G. & Abdul-Sathar, E.I. & Maya, R., 2015. "Local linear estimation of residual entropy function of conditional distributions," Computational Statistics & Data Analysis, Elsevier, vol. 88(C), pages 1-14.

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