Characterizations of Proportional Hazard and Reversed Hazard Rate Models Based on Symmetric and Asymmetric Kullback-Leibler Divergences

Ghobad Barmalzan (), Narayanaswamy Balakrishnan and Hadi Saboori
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Ghobad Barmalzan: University of Zabol
Narayanaswamy Balakrishnan: McMaster University
Hadi Saboori: University of Zabol

Sankhya B: The Indian Journal of Statistics, 2019, vol. 81, issue 1, No 2, 26-38

Abstract: Abstract Kullback-Leibler divergence (Kℒ)$(\mathcal {K}\mathcal {L})$ is widely used for selecting the best model from a given set of candidate parametrized probabilistic models as an approximation to the true density function h(·). In this paper, we obtain a necessary and sufficient condition to determine proportional hazard and reversed hazard rate models based on symmetric and asymmetric Kullback-Leibler divergences. Obtained results show that if h belongs to proportional hazard rate (reversed hazard) model, then the Kullback-Leibler divergence between h and baseline density function, f0, is independent of the choice of ξ, the cut point of left (right) truncated distribution.

Keywords: Symmetric Kullback-Leibler divergence; Asymmetric Kullback-Leibler divergence; Proportional hazard rate model; Proportional reversed hazard rate model.; Primary 62E10; Secondary 62F30 (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1007/s13571-017-0144-z

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