Kumaraswamy distribution: different methods of estimation

Sanku Dey, Josmar Mazucheli, Saralees Nadarajah

    Research output: Contribution to journalArticlepeer-review


    This paper addresses different methods of estimation of the unknown parameters of a two-parameter Kumaraswamy distribution from a frequentist point of view. We briefly describe ten different frequentist approaches, namely, maximum likelihood estimators, moments estimators, L-moments estimators, percentile based estimators, least squares estimators, weighted least squares estimators, maximum product of spacings estimators, Cramér–von-Mises estimators, Anderson–Darling estimators and right tailed Anderson–Darling estimators. Monte Carlo simulations and two real data applications are performed to compare the performances of the estimators for both small and large samples.

    Original languageEnglish
    Pages (from-to)2094-2111
    Number of pages18
    JournalComputational and Applied Mathematics
    Issue number2
    Early online date29 Mar 2017
    Publication statusPublished - May 2018


    • Kumaraswamy distribution
    • Least squares estimators
    • Maximum likelihood estimators
    • Method of maximum product spacing
    • Method of moments estimators
    • Percentile estimators
    • Weighted least squares estimators


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