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A conditional perspective of weighted variance estimation of the optimal regression estimator
Linköping University, The Institute of Technology. Linköping University, Department of Mathematics, Mathematical Statistics .
2006 (English)In: Journal of Statistical Planning and Inference, ISSN 0378-3758, Vol. 136, no 1, 221-234 p.Article in journal (Refereed) Published
Abstract [en]

The estimation of the variance for the GREG (general regression) estimator by weighted residuals is widely accepted as a method which yields estimators with good conditional properties. Since the optimal (regression) estimator shares the properties of GREG estimators which are used in the construction of weighted variance estimators, we introduce the weighting procedure also for estimating the variance of the optimal estimator. This method of variance estimation was originally presented in a seemingly ad hoc manner, and we shall discuss it from a conditional point of view and also look at an alternative way of utilizing the weights. Examples that stress conditional behaviour of estimators are then given for elementary sampling designs such as simple random sampling, stratified simple random sampling and Poisson sampling, where for the latter design we have conducted a small simulation study. © 2004 Elsevier B.V. All rights reserved.

Place, publisher, year, edition, pages
2006. Vol. 136, no 1, 221-234 p.
Keyword [en]
Conditional inference, GREG estimator, Poisson sampling
National Category
Engineering and Technology
URN: urn:nbn:se:liu:diva-50329DOI: 10.1016/j.jspi.2004.06.024OAI: diva2:271225
Available from: 2009-10-11 Created: 2009-10-11 Last updated: 2011-01-11

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Andersson, Per Gösta
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The Institute of TechnologyMathematical Statistics
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