Fitting the generalized logistic distribution by LQ-moments
The method of LQ-moments (LQMOM) for estimating parameters and quantiles of the Generalized Logistic (GL) distribution are introduced. We explore and extend 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 ker...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Published: |
Springer New York
2011
|
| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/44928/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | Universiti Teknologi Malaysia |
| id |
my.utm.44928 |
|---|---|
| record_format |
eprints |
| spelling |
my.utm.449282017-01-31T06:58:41Z http://eprints.utm.my/id/eprint/44928/ Fitting the generalized logistic distribution by LQ-moments Shabri, Ani Jemain, Abdul Aziz U Military Science The method of LQ-moments (LQMOM) for estimating parameters and quantiles of the Generalized Logistic (GL) distribution are introduced. We explore and extend 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 is proposed to estimate the quantile function. A comparison of these methods is done by simulation. The performances of the proposed estimators of the GL distribution was compared with the estimators based on L-moments for various sample sizes and return periods. The overall results show the LQMOM provides better results only for small or moderate sample size. Springer New York 2011 Article PeerReviewed Shabri, Ani and Jemain, Abdul Aziz (2011) Fitting the generalized logistic distribution by LQ-moments. Applied Mathematical Sciences, 5 (53-56). pp. 2663-2676. ISSN 1312-885X |
| institution |
Universiti Teknologi Malaysia |
| building |
UTM Library |
| collection |
Institutional Repository |
| continent |
Asia |
| country |
Malaysia |
| content_provider |
Universiti Teknologi Malaysia |
| content_source |
UTM Institutional Repository |
| url_provider |
http://eprints.utm.my/ |
| topic |
U Military Science |
| spellingShingle |
U Military Science Shabri, Ani Jemain, Abdul Aziz Fitting the generalized logistic distribution by LQ-moments |
| description |
The method of LQ-moments (LQMOM) for estimating parameters and quantiles of the Generalized Logistic (GL) distribution are introduced. We explore and extend 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 is proposed to estimate the quantile function. A comparison of these methods is done by simulation. The performances of the proposed estimators of the GL distribution was compared with the estimators based on L-moments for various sample sizes and return periods. The overall results show the LQMOM provides better results only for small or moderate sample size. |
| format |
Article |
| author |
Shabri, Ani Jemain, Abdul Aziz |
| author_facet |
Shabri, Ani Jemain, Abdul Aziz |
| author_sort |
Shabri, Ani |
| title |
Fitting the generalized logistic distribution by LQ-moments |
| title_short |
Fitting the generalized logistic distribution by LQ-moments |
| title_full |
Fitting the generalized logistic distribution by LQ-moments |
| title_fullStr |
Fitting the generalized logistic distribution by LQ-moments |
| title_full_unstemmed |
Fitting the generalized logistic distribution by LQ-moments |
| title_sort |
fitting the generalized logistic distribution by lq-moments |
| publisher |
Springer New York |
| publishDate |
2011 |
| url |
http://eprints.utm.my/id/eprint/44928/ |
| _version_ |
1643651589060165632 |