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Kumaraswamy distribution: different methods of estimation

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Abstract

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.

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Authors and Affiliations

  1. St. Anthony’s College, Shillong, 793001, India

    Sanku Dey

  2. Universidade Estadual de Maringá, Maringá, Brazil

    Josmar Mazucheli

  3. University of Manchester, Manchester, M13 9PL, UK

    Saralees Nadarajah

Authors
  1. Sanku Dey
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  2. Josmar Mazucheli
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  3. Saralees Nadarajah
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Corresponding author

Correspondence to Saralees Nadarajah.

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Communicated by Eduardo Souza de Cursi.

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Dey, S., Mazucheli, J. & Nadarajah, S. Kumaraswamy distribution: different methods of estimation. Comp. Appl. Math. 37, 2094–2111 (2018). https://doi.org/10.1007/s40314-017-0441-1

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