A study of methods for estimating in the exponentiated Gumbel distribution

DOI

10.2991/jsta.2017.16.1.7How to use a DOI?

Keywords

Uniform minimum variance unbiased estimator; Maximum likelihood estimator; Least squares estimator;Weight least squares estimator; Percentile estimator; Model selection criteria; Exponentiated Gumbel distribution.

Abstract

The exponentiated Gumbel model has been shown to be useful in climate modeling including global warming problem, flood frequency analysis, offshore modeling, rainfall modeling and wind speed modeling. Here, we consider estimation of the PDF and the CDF of the exponentiated Gumbel distribution. The following esti- mators are considered: uniformly minimum variance unbiased (UMVU) estimator, maximum likelihood (ML) estimator, percentile (PC) estimator, least squares (LS) estimator and weighted least squares (WLS) estimator. Analytical expressions are derived for the bias and the mean squared error. Simulation studies and real data applications show that the ML estimator performs better than others.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - JOUR
AU  - K. Fathi
AU  - S.F. Bagheri
AU  - M. Alizadeh
AU  - M. Alizadeh
PY  - 2017
DA  - 2017/03/01
TI  - A study of methods for estimating in the exponentiated Gumbel distribution
JO  - Journal of Statistical Theory and Applications
SP  - 81
EP  - 95
VL  - 16
IS  - 1
SN  - 2214-1766
UR  - https://doi.org/10.2991/jsta.2017.16.1.7
DO  - 10.2991/jsta.2017.16.1.7
ID  - Fathi2017
ER  -