A Class of Estimators for Finite Population Mean in Double Sampling under Nonresponse Using Fractional Raw Moments | Zendy

Manzoor Khan | Zendy; Javid Shabbir | Zendy; Zawar Hussain | Zendy; Bander Al-Zahrani | Zendy

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A Class of Estimators for Finite Population Mean in Double Sampling under Nonresponse Using Fractional Raw Moments

Author(s) -

Manzoor Khan,

Javid Shabbir,

Zawar Hussain,

Bander Al-Zahrani

Publication year - 2014

Publication title -

journal of applied mathematics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.307

H-Index - 43

eISSN - 1687-0042

pISSN - 1110-757X

DOI - 10.1155/2014/282065

Subject(s) - estimator , mathematics , extremum estimator , mean squared error , class (philosophy) , statistics , population , ratio estimator , m estimator , sampling (signal processing) , efficient estimator , computer science , minimum variance unbiased estimator , artificial intelligence , demography , filter (signal processing) , sociology , computer vision

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

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