LQ-Moments: application to the log-normal distribution
Mudolkar and Hutson (1998) extended L-moments to new moment like entitles called LQmoments (LQMOM). The objective of this paper is to develop improved LQMOM that do not impose restrictions on the value of p and a such as the median, trimean or the Gastwirth but we explore an extended class of LQMOM...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Science Publications
2006
|
| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/3794/1/AniShabri2006_LQMomentsApplicationtotheLogNormal.pdf http://eprints.utm.my/id/eprint/3794/ http://www.scipub.org/fulltext/jms2/jms223414-421.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | Universiti Teknologi Malaysia |
| Language: | English |
| Summary: | Mudolkar and Hutson (1998) extended L-moments to new moment like entitles called LQmoments (LQMOM). The objective of this paper is to develop improved LQMOM that do not impose restrictions on the value of p and a such as the median, trimean or the Gastwirth but we explore an extended class of LQMOM with consideration combinations of p and a 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. Monte Carlo simulations are conducted to illustrate the performance of the proposed estimators of the log-normal 3 (LN3) distribution were compared with the estimators based on conventional LMOM and MOM (method of moments) for various sample sizes and return periods. |
|---|