Estimation of the extreme value type i distribution by the method of LQ-moments

Ani Shabri, Abdul Aziz Jemain

Research output: Contribution to journalArticle

4 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)298-304
Number of pages7
JournalJournal of Mathematics and Statistics
Volume5
Issue number4
DOIs
Publication statusPublished - 2009

Fingerprint

Extreme Values
Moment
Sample Size
Generalized lambda Distribution
L-moments
Moment Method
Quantile
Tail
Estimator

Keywords

  • L-moments
  • LQ-moments
  • Quick estimator
  • The weighted kernel quantile
  • Upper tail

ASJC Scopus subject areas

  • Mathematics(all)
  • Statistics and Probability

Cite this

Estimation of the extreme value type i distribution by the method of LQ-moments. / Shabri, Ani; Jemain, Abdul Aziz.

In: Journal of Mathematics and Statistics, Vol. 5, No. 4, 2009, p. 298-304.

Research output: Contribution to journalArticle

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