A Class of Estimators for Finite Population Mean in Double Sampling under Nonresponse Using Fractional Raw Moments
This paper presents new classes of estimators in estimating the finite population mean under double sampling in the presence of nonresponse when using information on fractional raw moments. The expressions for mean square error of the proposed classes of estimators are derived up to the first degree...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2014-01-01
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| Series: | Journal of Applied Mathematics |
| Online Access: | http://dx.doi.org/10.1155/2014/282065 |
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| _version_ | 1832567212496388096 |
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| author | Manzoor Khan Javid Shabbir Zawar Hussain Bander Al-Zahrani |
| author_facet | Manzoor Khan Javid Shabbir Zawar Hussain Bander Al-Zahrani |
| author_sort | Manzoor Khan |
| collection | DOAJ |
| description | This paper presents new classes of estimators in estimating the finite population mean under double sampling in the presence of nonresponse when using information on fractional raw moments. The expressions for mean square error of the proposed classes of estimators are derived up to the first degree of approximation. It is shown that a proposed class of estimators performs better than the usual mean estimator, ratio type estimators, and Singh and Kumar (2009) estimator. An empirical study is carried out to demonstrate the performance of a proposed class of estimators. |
| format | Article |
| id | doaj-art-06ca96fbaf5f4510bcdb70c60822bea6 |
| institution | Kabale University |
| issn | 1110-757X 1687-0042 |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Applied Mathematics |
| spelling | doaj-art-06ca96fbaf5f4510bcdb70c60822bea62025-02-03T01:02:02ZengWileyJournal of Applied Mathematics1110-757X1687-00422014-01-01201410.1155/2014/282065282065A Class of Estimators for Finite Population Mean in Double Sampling under Nonresponse Using Fractional Raw MomentsManzoor Khan0Javid Shabbir1Zawar Hussain2Bander Al-Zahrani3Department of Statistics, Quaid-i-Azam University, Islamabad 45320, PakistanDepartment of Statistics, Quaid-i-Azam University, Islamabad 45320, PakistanDepartment of Statistics, Quaid-i-Azam University, Islamabad 45320, PakistanDepartment of Statistics, King Abdulaziz University, P.O. Box 80203, Jeddah 21589, Saudi ArabiaThis paper presents new classes of estimators in estimating the finite population mean under double sampling in the presence of nonresponse when using information on fractional raw moments. The expressions for mean square error of the proposed classes of estimators are derived up to the first degree of approximation. It is shown that a proposed class of estimators performs better than the usual mean estimator, ratio type estimators, and Singh and Kumar (2009) estimator. An empirical study is carried out to demonstrate the performance of a proposed class of estimators.http://dx.doi.org/10.1155/2014/282065 |
| spellingShingle | Manzoor Khan Javid Shabbir Zawar Hussain Bander Al-Zahrani A Class of Estimators for Finite Population Mean in Double Sampling under Nonresponse Using Fractional Raw Moments Journal of Applied Mathematics |
| title | A Class of Estimators for Finite Population Mean in Double Sampling under Nonresponse Using Fractional Raw Moments |
| title_full | A Class of Estimators for Finite Population Mean in Double Sampling under Nonresponse Using Fractional Raw Moments |
| title_fullStr | A Class of Estimators for Finite Population Mean in Double Sampling under Nonresponse Using Fractional Raw Moments |
| title_full_unstemmed | A Class of Estimators for Finite Population Mean in Double Sampling under Nonresponse Using Fractional Raw Moments |
| title_short | A Class of Estimators for Finite Population Mean in Double Sampling under Nonresponse Using Fractional Raw Moments |
| title_sort | class of estimators for finite population mean in double sampling under nonresponse using fractional raw moments |
| url | http://dx.doi.org/10.1155/2014/282065 |
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