Estimation of location and scale parameters in two-parameter exponential distribution based on ranked set sample

In this article, we are interested in simultaneous comparison of the location and scale estimators of a two-parameter exponential distribution based on simple random sample (SRS) and ranked set sample (RSS) by using generalized variance (GV). We suggest various RSS strategies to estimate the scale p...

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Main Authors: Sukuman Sarikavanij, Subramanyam Kasala, Bimal K. Sinha, Montip Tiensuwan
Other Authors: King Mongkuts University of Technology Thonburi
Format: Article
Published: 2018
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Online Access:https://repository.li.mahidol.ac.th/handle/123456789/34147
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spelling th-mahidol.341472018-11-09T09:31:21Z Estimation of location and scale parameters in two-parameter exponential distribution based on ranked set sample Sukuman Sarikavanij Subramanyam Kasala Bimal K. Sinha Montip Tiensuwan King Mongkuts University of Technology Thonburi The University of North Carolina Wilmington University of Maryland, Baltimore County Mahidol University South Carolina Commission on Higher Education Mathematics In this article, we are interested in simultaneous comparison of the location and scale estimators of a two-parameter exponential distribution based on simple random sample (SRS) and ranked set sample (RSS) by using generalized variance (GV). We suggest various RSS strategies to estimate the scale parameter. Their performances in terms of GV are compared with SRS strategy. Finally, we illustrate the minimum values of set size, n, based on RSS, which would result in smaller GV than that based on SRS. © 2014 Taylor and Francis Group, LLC. 2018-11-09T02:31:21Z 2018-11-09T02:31:21Z 2014-01-01 Article Communications in Statistics: Simulation and Computation. Vol.43, No.1 (2014), 132-141 10.1080/03610918.2012.698776 15324141 03610918 2-s2.0-84882414540 https://repository.li.mahidol.ac.th/handle/123456789/34147 Mahidol University SCOPUS https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84882414540&origin=inward
institution Mahidol University
building Mahidol University Library
continent Asia
country Thailand
Thailand
content_provider Mahidol University Library
collection Mahidol University Institutional Repository
topic Mathematics
spellingShingle Mathematics
Sukuman Sarikavanij
Subramanyam Kasala
Bimal K. Sinha
Montip Tiensuwan
Estimation of location and scale parameters in two-parameter exponential distribution based on ranked set sample
description In this article, we are interested in simultaneous comparison of the location and scale estimators of a two-parameter exponential distribution based on simple random sample (SRS) and ranked set sample (RSS) by using generalized variance (GV). We suggest various RSS strategies to estimate the scale parameter. Their performances in terms of GV are compared with SRS strategy. Finally, we illustrate the minimum values of set size, n, based on RSS, which would result in smaller GV than that based on SRS. © 2014 Taylor and Francis Group, LLC.
author2 King Mongkuts University of Technology Thonburi
author_facet King Mongkuts University of Technology Thonburi
Sukuman Sarikavanij
Subramanyam Kasala
Bimal K. Sinha
Montip Tiensuwan
format Article
author Sukuman Sarikavanij
Subramanyam Kasala
Bimal K. Sinha
Montip Tiensuwan
author_sort Sukuman Sarikavanij
title Estimation of location and scale parameters in two-parameter exponential distribution based on ranked set sample
title_short Estimation of location and scale parameters in two-parameter exponential distribution based on ranked set sample
title_full Estimation of location and scale parameters in two-parameter exponential distribution based on ranked set sample
title_fullStr Estimation of location and scale parameters in two-parameter exponential distribution based on ranked set sample
title_full_unstemmed Estimation of location and scale parameters in two-parameter exponential distribution based on ranked set sample
title_sort estimation of location and scale parameters in two-parameter exponential distribution based on ranked set sample
publishDate 2018
url https://repository.li.mahidol.ac.th/handle/123456789/34147
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