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Journal of Applied Sciences
  Year: 2006 | Volume: 6 | Issue: 5 | Page No.: 993-997
DOI: 10.3923/jas.2006.993.997
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LQ-moments: Application to the Extreme Value Type I Distribution

Ani Shabri and Abdul Aziz Jemain

The objective of this study is to develop improved LQ-moments that do not impose restrictions on the value of p and α such as the median, trimean or the Gastwirth but we explore an extended class of LQMOM with consideration combinations of p and α values in the range 0 and 0.5. The popular quantile estimator namely the Weighted Kernel Quantile (WKQ) estimator will be proposed to estimate the quantile function. The performances of the proposed estimators of the Extreme Values Type 1 (EV1) distribution were compared with the estimators based on conventional LMOM, MOM (method of moments), ML (method of maximum likelihood) and the LQ-moments based on LIQ (linear interpolation quantile) for various sample sizes and return periods.
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How to cite this article:

Ani Shabri and Abdul Aziz Jemain , 2006. LQ-moments: Application to the Extreme Value Type I Distribution. Journal of Applied Sciences, 6: 993-997.

DOI: 10.3923/jas.2006.993.997






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