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On estimation of two-component mixture inverse Lomax model via Bayesian approach

Author

Listed:
  • Jafer Rahman

    (Hazara University)

  • Muhammad Aslam

    (Riphah International University)

Abstract

A mixture distribution is the probability distribution of observations in the pooled population which is used to make statistical inferences about the characteristics of the sub-populations on the basis of sample data from the joint population. This article comprises such sort of study for unknown parameters of two-component mixture inverse Lomax distribution based on Bayesian thoughts. Bayes estimators and Bayes posterior risks for the parameters are derived under various loss functions along with the use of conjugate priors. Numerical results for Bayes estimates and Bayes risks are obtained by simulation as well as real data. The study also includes Maximum likelihood estimation for the comparisons with Bayesian estimation.

Suggested Citation

  • Jafer Rahman & Muhammad Aslam, 2017. "On estimation of two-component mixture inverse Lomax model via Bayesian approach," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 8(1), pages 99-109, January.
    • Handle: RePEc:spr:ijsaem:v:8:y:2017:i:1:d:10.1007_s13198-014-0296-4
    DOI: 10.1007/s13198-014-0296-4
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    References listed on IDEAS

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    1. Syed Mohsin Ali Kazmi & Muhammad Aslam & Sajid Ali & Nasir Abbas, 2013. "Selection of suitable prior for the Bayesian mixture of a class of lifetime distributions under type-I censored datasets," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(8), pages 1639-1658, August.
    2. Kleiber, Christian, 2002. "Lorenz ordering of order statistics from log-logistic and related distributions," Technical Reports 2002,09, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    3. M. Saleem & M. Aslam & P. Economou, 2010. "On the Bayesian analysis of the mixture of power function distribution using the complete and the censored sample," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(1), pages 25-40.
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    Cited by:

    1. Hanieh Panahi, 2019. "Estimation for the parameters of the Burr Type XII distribution under doubly censored sample with application to microfluidics data," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 10(4), pages 510-518, August.

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