Open AccessAlmost Unbiased Estimation Procedures of Population Mean in Two- Occasion Successive Sampling
Author(s) -
G. N. Singh,
Ajeet Kumar Singh,
Cem Kadılar
Publication year - 2016
Publication title -
hacettepe journal of mathematics and statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.312
H-Index - 26
ISSN - 1303-5010
DOI - 10.15672/hjms.2016.391
Subject(s) - mathematics , statistics , population mean , unbiased estimation , best linear unbiased prediction , estimation , sampling (signal processing) , u statistic , population , minimum variance unbiased estimator , mean squared error , estimator , demography , selection (genetic algorithm) , management , filter (signal processing) , artificial intelligence , sociology , computer science , economics , computer vision
The objective of this paper is to construct some unbiased estimators of the current population mean in two-occasion successive sampling. Utilizing the readily available information on an auxiliary variable on both occasions, almost unbiased ratio and regression cum exponential type estimators of current population mean have been proposed. The oretical properties of the proposed estimation procedures have been examined and their respective optimum replacement strategies are for mulated. Performances of the proposed estimators are empirically com pared with (i) the sample mean estimator, when no sample units were matched from the previous occasion and (ii) natural successive sampling estimator when no auxiliary information was used on any occasion. Em pirical results are critically interpreted and suitable recommendations are made to the survey practitioners for their practical applications.
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