Full information efficient estimator of finite population variance

Manoj Kumar Srivastava; Namita Srivastava; Housila P. Singh

Manoj Kumar Srivastava Associate Professor, Department of Statistics, Institute of Social Sciences, Dr. BRA University, Agra-282002.U.P. India , Namita Srivastava Associate Professor, Department of Statistics, St. John's College, Agra-282002, U.P. India , Housila P. Singh Professor, School of Studies in Statistics, Vikram University, Ujjain-456010, M.P. India Statistics in Transition new series, vol. 10, 2009, 3, pages: 415-435 Published online: 1 December 2009

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ABSTRACT

Second order or quadratic and finite population parametric functions may be expressed as total of variable-values on pairs of units in a derived population. Recently, Sitter and Wu (2002) utilized this approach for estimating variance under model calibration. In this paper an efficient design based full-information estimator of finite population variance has been suggested. The exact expression of its variance and its relative efficiency has also been derived. Finally, the proposed estimator has been shown to be superior to its competitors in an empirical investigation.

KEYWORDS

design based estimation; variance estimation; Rao-Blackwellization in survey sampling; estimation of polynomial finite population function.

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