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ISSN: 1549-3644 (Print)
ISSN: 1558-6359 (Online)
Research Article Open Access

Estimation of the Extreme Value Type I Distribution by the Method of LQ-Moments

Ani Shabri and Abdul Aziz Jemain

Abstract

Problem statement: The study evaluated the effectiveness of the various quantile estimators of the LQ-moments method for estimating parameters of the Extreme Value Type 1 (EV1) distribution. Approach: The performances of the LQ-moments were analyzed and compared against a widely used method of L-moments by using simulated samples of both EV1 and generalized Lambda distribution, focusing on small and moderate sample sizes. Results: The analysis results showed that LQMOM method wais more efficient in many cases especially for the upper tails of the distribution and for various sample sizes. Conclusion: This study demonstrated that conventional LMOM was not optimal for the estimation of the EV1 distribution.

Journal of Mathematics and Statistics
Volume 5 No. 4, 2009, 298-304

DOI: https://doi.org/10.3844/jmssp.2009.298.304

Submitted On: 7 August 2009 Published On: 31 December 2009

How to Cite: Shabri, A. & Jemain, A. A. (2009). Estimation of the Extreme Value Type I Distribution by the Method of LQ-Moments. Journal of Mathematics and Statistics, 5(4), 298-304. https://doi.org/10.3844/jmssp.2009.298.304

Open AccessCopyright: © 2009 Ani Shabri and Abdul Aziz Jemain. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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Keywords

  • The Weighted kernel quantile
  • upper tail
  • LQ-moments
  • L-moments
  • quick estimator