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Estimation stage in survey sampling: a multiparameter approach. (English) Zbl 07578288

Summary: Most of the real applications in survey sampling involve not one, but several characteristics of study. In this paper, a unified framework of joint estimation of the parameters of interest is presented under various sampling designs. The applications of the results of this research entails a significant gain in computational efficiency.

MSC:

62-XX Statistics

Software:

R; sampling

References:

[1] Cassady, R. J. & Valiant, R. (1993), ‘Conditional Properties of Poststratified Estimators under Normal Theory´, Survey Methodology 19, 183-192.
[2] Gupta, A. K. & Nagar, D. K. (2000), Matrix Variate Distributions, Chapmann and Hall, New York, United States. · Zbl 0935.62064
[3] Holmberg, A. (2002a), ‘A Multiparameter Perspective on the Choice of Sampling Design in Surveys´, Statistics in Transition 5, 969-994.
[4] Holmberg, A. (2002b), On the Choice of Sampling Design under GREG Estimation in Multiparameter Surveys, 1, RD Department, Statistics Sweden, SE-701 89 Örebro, Sweden.
[5] Lavallée, P. & Caron, P. (2001), ‘Estimation Using the Generalized Weigth Share Method: The use of Record Linkage´, Survey Methodology 27, 155-169.
[6] R Development Core Team, (2008), R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0. *http://www.R-project.org
[7] S\arndal, (), .
[8] Tillé, Y. & Matei, A. (2008), Sampling: Survey Sampling. R package version 2.0. · Zbl 1161.62311
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