Improved estimation of population variance using information on auxiliary attribute in simple random sampling

Singh and Kumar (2011) [19] suggested estimators for calculating population variance using auxiliary attributes. This paper proposes a family of estimators based on an adaptation of the estimators presented by Kadilar and Cingi (2004) [5] and Singh et al. (2007) [16], and introduces a new family of...

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Bibliographic Details
Published inApplied mathematics and computation Vol. 235; pp. 43 - 49
Main Authors Singh, Rajesh, Malik, Sachin
Format Journal Article
LanguageEnglish
Published Elsevier Inc 25.05.2014
Subjects
Adaptation
Auxiliary attributes
Efficiency
Errors
Estimators
Mathematical analysis
Mathematical models
Mean square error
Mean square values
Population variance
Random sampling
Simple random sampling
Variance
Auxiliary attributes
Population variance
Simple random sampling
Efficiency
Mean square error
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Summary:Singh and Kumar (2011) [19] suggested estimators for calculating population variance using auxiliary attributes. This paper proposes a family of estimators based on an adaptation of the estimators presented by Kadilar and Cingi (2004) [5] and Singh et al. (2007) [16], and introduces a new family of estimators using auxiliary attributes. The expressions of the mean square errors (MSEs) of the adapted and proposed families are derived. It is shown that adapted estimators and suggested estimators are more efficient than Singh and Kumar (2011) [19] estimators. The theoretical findings are supported by a numerical example.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:0096-3003
1873-5649
DOI:10.1016/j.amc.2014.03.002