A family of ratio estimators for population mean in extreme ranked set sampling using two auxiliary variables

In this paper we have adopted the Khoshnevisan et al. (2007) family of estimators to extreme ranked set sampling (ERSS) using information on single and two auxiliary variables. Expressions for mean square error (MSE) of proposed estimators are derived to first order of approximation. Monte Carlo sim...

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Detalles Bibliográficos
Autores: Haq, Abdul, Shabbir, Javid
Tipo de recurso: artículo
Fecha de publicación:2010
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2099/11221
Acceso en línea:https://hdl.handle.net/2099/11221
Access Level:acceso abierto
Palabra clave:Sampling (Statistics)
Ratio estimator
Ranked set sampling
Extreme ranked set sampling.
Mostreig (Estadística)
Classificació AMS::62 Statistics::62D05 Sampling theory, sample surveys
Àrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica
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spelling A family of ratio estimators for population mean in extreme ranked set sampling using two auxiliary variablesHaq, AbdulShabbir, JavidSampling (Statistics)Ratio estimatorRanked set samplingExtreme ranked set sampling.Mostreig (Estadística)Classificació AMS::62 Statistics::62D05 Sampling theory, sample surveysÀrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàticaIn this paper we have adopted the Khoshnevisan et al. (2007) family of estimators to extreme ranked set sampling (ERSS) using information on single and two auxiliary variables. Expressions for mean square error (MSE) of proposed estimators are derived to first order of approximation. Monte Carlo simulations and real data sets have been used to illustrate the method. The results indicate that the estimators under ERSS are more efficient as compared to estimators based on simple random sampling (SRS), when the underlying populations are symmetric.Peer ReviewedInstitut d'Estadística de Catalunya20102010-01-0120112011-10-28journal articlehttp://purl.org/coar/resource_type/c_6501NAhttp://purl.org/coar/version/c_be7fb7dd8ff6fe43info:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/2099/11221reponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2Attribution-NonCommercial-NoDerivs 3.0 Spainhttp://creativecommons.org/licenses/by-nc-nd/3.0/es/info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2099/112212026-05-27T15:37:01Z
dc.title.none.fl_str_mv A family of ratio estimators for population mean in extreme ranked set sampling using two auxiliary variables
title A family of ratio estimators for population mean in extreme ranked set sampling using two auxiliary variables
spellingShingle A family of ratio estimators for population mean in extreme ranked set sampling using two auxiliary variables
Haq, Abdul
Sampling (Statistics)
Ratio estimator
Ranked set sampling
Extreme ranked set sampling.
Mostreig (Estadística)
Classificació AMS::62 Statistics::62D05 Sampling theory, sample surveys
Àrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica
title_short A family of ratio estimators for population mean in extreme ranked set sampling using two auxiliary variables
title_full A family of ratio estimators for population mean in extreme ranked set sampling using two auxiliary variables
title_fullStr A family of ratio estimators for population mean in extreme ranked set sampling using two auxiliary variables
title_full_unstemmed A family of ratio estimators for population mean in extreme ranked set sampling using two auxiliary variables
title_sort A family of ratio estimators for population mean in extreme ranked set sampling using two auxiliary variables
dc.creator.none.fl_str_mv Haq, Abdul
Shabbir, Javid
author Haq, Abdul
author_facet Haq, Abdul
Shabbir, Javid
author_role author
author2 Shabbir, Javid
author2_role author
dc.subject.none.fl_str_mv Sampling (Statistics)
Ratio estimator
Ranked set sampling
Extreme ranked set sampling.
Mostreig (Estadística)
Classificació AMS::62 Statistics::62D05 Sampling theory, sample surveys
Àrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica
topic Sampling (Statistics)
Ratio estimator
Ranked set sampling
Extreme ranked set sampling.
Mostreig (Estadística)
Classificació AMS::62 Statistics::62D05 Sampling theory, sample surveys
Àrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica
description In this paper we have adopted the Khoshnevisan et al. (2007) family of estimators to extreme ranked set sampling (ERSS) using information on single and two auxiliary variables. Expressions for mean square error (MSE) of proposed estimators are derived to first order of approximation. Monte Carlo simulations and real data sets have been used to illustrate the method. The results indicate that the estimators under ERSS are more efficient as compared to estimators based on simple random sampling (SRS), when the underlying populations are symmetric.
publishDate 2010
dc.date.none.fl_str_mv 2010
2010-01-01
2011
2011-10-28
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
NA
http://purl.org/coar/version/c_be7fb7dd8ff6fe43
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/2099/11221
url https://hdl.handle.net/2099/11221
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-NoDerivs 3.0 Spain
http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-NoDerivs 3.0 Spain
http://creativecommons.org/licenses/by-nc-nd/3.0/es/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Institut d'Estadística de Catalunya
publisher.none.fl_str_mv Institut d'Estadística de Catalunya
dc.source.none.fl_str_mv reponame:UPCommons. Portal del coneixement obert de la UPC
instname:Universitat Politècnica de Catalunya (UPC)
instname_str Universitat Politècnica de Catalunya (UPC)
reponame_str UPCommons. Portal del coneixement obert de la UPC
collection UPCommons. Portal del coneixement obert de la UPC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,301603

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