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Optimal variance estimation for generalized regression predictor

โœ Scribed by Arijit Chaudhuri; Debesh Roy

Publisher
Elsevier Science
Year
1997
Tongue
English
Weight
760 KB
Volume
60
Category
Article
ISSN
0378-3758

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โœฆ Synopsis

The generalized regression (greg) predictor for the finite population total of a real variable is often employed when values of an auxiliary variable are available. Several variance estimators for it do well in large samples though bearing no optimality properties. We find a variance estimator which, under a restrictive model, has an optimality property under 'exact' as well as 'asymptotic' analysis. But this involves model parameters. Under a further restriction on the model, two model-parameter-free variance estimators are derived sharing the same 'asymptotic' optimality. Numerical illustrations through simulation are presented to demonstrate marginal improvements in using them rather than their predecessors. Two of the latter, though not optimal, are simpler, intuitively appealing, compete well in large samples, generally applicable and should be persisted with in practice.

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