A Class of Improved Estimators for Estimating Population Mean Regarding Partial Information in Double Sampling

1
Aamir Sanaullah
Aamir Sanaullah
2
Dr. Saleha Shouket
Dr. Saleha Shouket
3
Hina Khan
Hina Khan
1 GC University, Lahore, Pakistan.

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In this paper a class of improved estimators has been proposed for estimating population mean in two phase (double) sampling when only partial information is available on either of two auxiliary variables. Under simple random sampling (SRWOR), expressions of mean square error and bias have been derived to make comparison of suggested class with wide range of other estimators. Empirical study has also been given using five different natural populations. Empirical study confirmed that the suggested class of improved estimators is more efficient under percent relative efficiency (PRE) criterion.

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No external funding was declared for this work.

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The authors declare no conflict of interest.

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No ethics committee approval was required for this article type.

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Not applicable for this article.

Aamir Sanaullah. 2013. \u201cA Class of Improved Estimators for Estimating Population Mean Regarding Partial Information in Double Sampling\u201d. Global Journal of Science Frontier Research - F: Mathematics & Decision GJSFR-F Volume 12 (GJSFR Volume 12 Issue F14): .

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GJSFR Volume 12 Issue F14
Pg. 33- 45
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Crossref Journal DOI 10.17406/GJSFR

Print ISSN 0975-5896

e-ISSN 2249-4626

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v1.2

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January 5, 2013

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English

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In this paper a class of improved estimators has been proposed for estimating population mean in two phase (double) sampling when only partial information is available on either of two auxiliary variables. Under simple random sampling (SRWOR), expressions of mean square error and bias have been derived to make comparison of suggested class with wide range of other estimators. Empirical study has also been given using five different natural populations. Empirical study confirmed that the suggested class of improved estimators is more efficient under percent relative efficiency (PRE) criterion.

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A Class of Improved Estimators for Estimating Population Mean Regarding Partial Information in Double Sampling

Dr. Saleha Shouket
Dr. Saleha Shouket
Hina Khan
Hina Khan
Aamir Sanaullah
Aamir Sanaullah GC University, Lahore, Pakistan.

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