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A class of bivariate models with proportional reversed hazard marginals

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Abstract

Recently the proportional reversed hazard model has received a considerable amount of attention in the statistical literature. The main aim of this paper is to introduce a bivariate proportional reversed hazard model and discuss its different properties. In most of the cases the joint probability distribution function can be expressed in compact forms. The maximum likelihood estimators cannot be expressed in explicit forms in most of the cases. EM algorithm has been proposed to compute the maximum likelihood estimators of the unknown parameters. For illustrative purposes two data sets have been analyzed and the performances are quite satisfactory.

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Acknowledgements

The authors would like to thank the referee and the editor Professor Ayanendranath Basu for their valuable comments.

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Authors and Affiliations

  1. Department of Mathematics and Statistics, Indian Institute of Technology Kanpur, Kanpur, Pin, 208016, India

    Debasis Kundu

  2. Department of Computer Science and Statistics, The University of New Brunswick at Saint John, New Brunswick, Canada, E2L 4L5

    Rameshwar D. Gupta

Authors
  1. Debasis Kundu
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  2. Rameshwar D. Gupta
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Corresponding author

Correspondence to Debasis Kundu.

Additional information

Part of Debasis Kundu’s work has been supported by a grant from the Department of Science and Technology, Government of India.

Part of Rameshwar D. Gupta’s work has been supported by a discovery grant from NSERC, Canada.

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Kundu, D., Gupta, R.D. A class of bivariate models with proportional reversed hazard marginals. Sankhya B 72, 236–253 (2010). https://doi.org/10.1007/s13571-011-0012-1

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