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Comparisons of Methods of Estimation for a New Pareto-type Distribution

Author

Listed:
  • Ali Saadati Nik

    (Department of Statistics, University of Mazandaran)

  • Akbar Asgharzadeh

    (Department of Statistics, University of Mazandaran)

  • Saralees Nadarajah

    (Department of Mathematics, University of Manchester)

Abstract

Bourguignon et al. (2016) introduced a new Pareto-type distribution to model income and reliability data. The aim of this paper is to estimate the parameters of this distribution from both frequentist and Bayesian view points. The maximum likelihood estimates, method of moment estimates, percentile estimates, least square and weighted least square estimates and maximum product of spacing estimates are considered as frequentist estimates. We have also considered the Bayes estimates of the unknown parameters and the associated credible intervals. The Bayes estimates are computed using an importance sampling method. To evaluate the performance of the different estimates, a Monte Carlo simulation study is carried out. Some real life data sets have been analyzed for illustrative purposes.

Suggested Citation

  • Ali Saadati Nik & Akbar Asgharzadeh & Saralees Nadarajah, 2019. "Comparisons of Methods of Estimation for a New Pareto-type Distribution," Statistica, Department of Statistics, University of Bologna, vol. 79(3), pages 291-319.
    • Handle: RePEc:bot:rivsta:v:79:y:2019:i:3:p:291-319
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    Cited by:

    1. Fanqun Li & Shanran Wei & Mingtao Zhao, 2023. "Bayesian Estimation of a New Pareto-Type Distribution Based on Mixed Gibbs Sampling Algorithm," Mathematics, MDPI, vol. 12(1), pages 1-13, December.
    2. Saadati Nik, A. & Asgharzadeh, A. & Raqab, Mohammad Z., 2021. "Estimation and prediction for a new Pareto-type distribution under progressive type-II censoring," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 190(C), pages 508-530.

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