@article {10.3844/jmssp.2009.298.304,
article_type = {journal},
title = {Estimation of the Extreme Value Type I Distribution by the Method of LQ-Moments},
author = {Shabri, Ani and Jemain, Abdul Aziz},
volume = {5},
year = {2009},
month = {Dec},
pages = {298-304},
doi = {10.3844/jmssp.2009.298.304},
url = {https://thescipub.com/abstract/jmssp.2009.298.304},
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 = {Journal of Mathematics and Statistics},
publisher = {Science Publications}
}