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Title: Kumaraswamy distribution: different methods of estimation

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.

Authors:
 [1];  [2];  [3]
  1. St. Anthony’s College (India)
  2. Universidade Estadual de Maringá (Brazil)
  3. University of Manchester (United Kingdom)
Publication Date:
OSTI Identifier:
22769319
Resource Type:
Journal Article
Journal Name:
Computational and Applied Mathematics
Additional Journal Information:
Journal Volume: 37; Journal Issue: 2; Other Information: Copyright (c) 2018 SBMAC - Sociedade Brasileira de Matemática Aplicada e Computacional; Country of input: International Atomic Energy Agency (IAEA); Journal ID: ISSN 0101-8205
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICAL METHODS AND COMPUTING; COMPUTERIZED SIMULATION; DISTRIBUTION; LEAST SQUARE FIT; MOMENTS METHOD; MONTE CARLO METHOD

Citation Formats

Dey, Sanku, Mazucheli, Josmar, and Nadarajah, Saralees. Kumaraswamy distribution: different methods of estimation. United States: N. p., 2018. Web. doi:10.1007/S40314-017-0441-1.
Dey, Sanku, Mazucheli, Josmar, & Nadarajah, Saralees. Kumaraswamy distribution: different methods of estimation. United States. doi:10.1007/S40314-017-0441-1.
Dey, Sanku, Mazucheli, Josmar, and Nadarajah, Saralees. Tue . "Kumaraswamy distribution: different methods of estimation". United States. doi:10.1007/S40314-017-0441-1.
@article{osti_22769319,
title = {Kumaraswamy distribution: different methods of estimation},
author = {Dey, Sanku and Mazucheli, Josmar and Nadarajah, Saralees},
abstractNote = {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.},
doi = {10.1007/S40314-017-0441-1},
journal = {Computational and Applied Mathematics},
issn = {0101-8205},
number = 2,
volume = 37,
place = {United States},
year = {2018},
month = {5}
}