An alternative estimator with appropriate plotting position estimates for the generalized exponential distribution

© 2020, Thai Statistical Association. All rights reserved. In this paper, we propose an alternative method for estimating generalized exponential distributions by applying plotting positions of modified percentile estimates. We compared its efficiency with the classical maximum likelihood estimator...

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Main Authors: Theerapong Kaewprasert, Manad Khamkong
Format: Journal
Published: 2020
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http://cmuir.cmu.ac.th/jspui/handle/6653943832/70703
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Institution: Chiang Mai University
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spelling th-cmuir.6653943832-707032020-10-14T08:39:41Z An alternative estimator with appropriate plotting position estimates for the generalized exponential distribution Theerapong Kaewprasert Manad Khamkong Mathematics © 2020, Thai Statistical Association. All rights reserved. In this paper, we propose an alternative method for estimating generalized exponential distributions by applying plotting positions of modified percentile estimates. We compared its efficiency with the classical maximum likelihood estimator and percentile estimator in terms of root mean square errors. Simulation results show that the percentile estimator outperformed the others for small sample sizes while the proposed estimator was most effective for medium to large sample sizes. This finding was supported by applying the proposed estimator to deduce whether Thai rainy season rainfall data followed a generalized exponential distribution from a rain gauging station in Fang district, Chiang Mai Province, Thailand. 2020-10-14T08:39:41Z 2020-10-14T08:39:41Z 2020-07-01 Journal 23510676 16859057 2-s2.0-85087355123 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85087355123&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/70703
institution Chiang Mai University
building Chiang Mai University Library
continent Asia
country Thailand
Thailand
content_provider Chiang Mai University Library
collection CMU Intellectual Repository
topic Mathematics
spellingShingle Mathematics
Theerapong Kaewprasert
Manad Khamkong
An alternative estimator with appropriate plotting position estimates for the generalized exponential distribution
description © 2020, Thai Statistical Association. All rights reserved. In this paper, we propose an alternative method for estimating generalized exponential distributions by applying plotting positions of modified percentile estimates. We compared its efficiency with the classical maximum likelihood estimator and percentile estimator in terms of root mean square errors. Simulation results show that the percentile estimator outperformed the others for small sample sizes while the proposed estimator was most effective for medium to large sample sizes. This finding was supported by applying the proposed estimator to deduce whether Thai rainy season rainfall data followed a generalized exponential distribution from a rain gauging station in Fang district, Chiang Mai Province, Thailand.
format Journal
author Theerapong Kaewprasert
Manad Khamkong
author_facet Theerapong Kaewprasert
Manad Khamkong
author_sort Theerapong Kaewprasert
title An alternative estimator with appropriate plotting position estimates for the generalized exponential distribution
title_short An alternative estimator with appropriate plotting position estimates for the generalized exponential distribution
title_full An alternative estimator with appropriate plotting position estimates for the generalized exponential distribution
title_fullStr An alternative estimator with appropriate plotting position estimates for the generalized exponential distribution
title_full_unstemmed An alternative estimator with appropriate plotting position estimates for the generalized exponential distribution
title_sort alternative estimator with appropriate plotting position estimates for the generalized exponential distribution
publishDate 2020
url https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85087355123&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/70703
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