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

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Keywords

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