Exponential Ratio Type Estimators In Stratified Random Sampling
Kadilar and Cingi (2003) have introduced a family of estimators using auxiliary information in stratified random sampling. In this paper, we propose the ratio estimator for the estimation of population mean in the stratified random sampling by using the estimators in Bahl and Tuteja (1991) and Kadil...
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creator | Singh, Rajesh Kumar, Mukesh Singh, R. D Chaudhry, M. K |
description | Kadilar and Cingi (2003) have introduced a family of estimators using
auxiliary information in stratified random sampling. In this paper, we propose
the ratio estimator for the estimation of population mean in the stratified
random sampling by using the estimators in Bahl and Tuteja (1991) and Kadilar
and Cingi (2003). Obtaining the mean square error (MSE) equations of the
proposed estimators, we find theoretical conditions that the proposed
estimators are more efficient than the other estimators. These theoretical
findings are supported by a numerical example. |
doi_str_mv | 10.48550/arxiv.1301.5086 |
format | Article |
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auxiliary information in stratified random sampling. In this paper, we propose
the ratio estimator for the estimation of population mean in the stratified
random sampling by using the estimators in Bahl and Tuteja (1991) and Kadilar
and Cingi (2003). Obtaining the mean square error (MSE) equations of the
proposed estimators, we find theoretical conditions that the proposed
estimators are more efficient than the other estimators. These theoretical
findings are supported by a numerical example.</description><identifier>DOI: 10.48550/arxiv.1301.5086</identifier><language>eng</language><subject>Mathematics - Statistics Theory ; Statistics - Theory</subject><creationdate>2013-01</creationdate><rights>http://arxiv.org/licenses/nonexclusive-distrib/1.0</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>228,230,780,885</link.rule.ids><linktorsrc>$$Uhttps://arxiv.org/abs/1301.5086$$EView_record_in_Cornell_University$$FView_record_in_$$GCornell_University$$Hfree_for_read</linktorsrc><backlink>$$Uhttps://doi.org/10.48550/arXiv.1301.5086$$DView paper in arXiv$$Hfree_for_read</backlink></links><search><creatorcontrib>Singh, Rajesh</creatorcontrib><creatorcontrib>Kumar, Mukesh</creatorcontrib><creatorcontrib>Singh, R. D</creatorcontrib><creatorcontrib>Chaudhry, M. K</creatorcontrib><title>Exponential Ratio Type Estimators In Stratified Random Sampling</title><description>Kadilar and Cingi (2003) have introduced a family of estimators using
auxiliary information in stratified random sampling. In this paper, we propose
the ratio estimator for the estimation of population mean in the stratified
random sampling by using the estimators in Bahl and Tuteja (1991) and Kadilar
and Cingi (2003). Obtaining the mean square error (MSE) equations of the
proposed estimators, we find theoretical conditions that the proposed
estimators are more efficient than the other estimators. These theoretical
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auxiliary information in stratified random sampling. In this paper, we propose
the ratio estimator for the estimation of population mean in the stratified
random sampling by using the estimators in Bahl and Tuteja (1991) and Kadilar
and Cingi (2003). Obtaining the mean square error (MSE) equations of the
proposed estimators, we find theoretical conditions that the proposed
estimators are more efficient than the other estimators. These theoretical
findings are supported by a numerical example.</abstract><doi>10.48550/arxiv.1301.5086</doi><oa>free_for_read</oa></addata></record> |
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title | Exponential Ratio Type Estimators In Stratified Random Sampling |
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