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                                       Details for article 57 of 88 found articles
 
 
  LQ-moments: Application to the Extreme Value Type I Distribution
 
 
Title: LQ-moments: Application to the Extreme Value Type I Distribution
Author: Ani Shabri
Abdul Aziz Jemain
Appeared in: Journal of applied sciences
Paging: Volume 6 (2006) nr. 5 pages 993-997
Year: 2006
Contents: 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.
Publisher: Asian Network for Scientific Information (provided by DOAJ)
Source file: Elektronische Wetenschappelijke Tijdschriften
 
 

                             Details for article 57 of 88 found articles
 
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