Towards optimal regression estimation in sample surveys
Towards optimal regression estimation in sample surveys
The Montanari (1987) regression estimator is optimal when the population regression coefficients are known. When the coefficients are estimated, the Montanari estimator is not optimal and can be extremely volatile. Using design-based arguments, this paper proposes a simpler and better alternative to the Montanari estimator that is also optimal when the population regression coefficients are known. Moreover, it can be easily implemented as it involves standard weighted least squares. The estimator is applicable under single stage stratified sampling with unequal probabilities within each stratum.
design-based inference, generalized regression estimator, inclusion probabilities, montanari estimator, conditional poisson sampling
319-329
Berger, Yves G.
8fd6af5c-31e6-4130-8b53-90910bf2f43b
Tirari, Mohammed E.H.
1e8a740b-fd06-49a2-aca7-c8ba6532b126
Tille, Yves
edb70ef7-07be-4fa5-a56c-8e31c5071197
2003
Berger, Yves G.
8fd6af5c-31e6-4130-8b53-90910bf2f43b
Tirari, Mohammed E.H.
1e8a740b-fd06-49a2-aca7-c8ba6532b126
Tille, Yves
edb70ef7-07be-4fa5-a56c-8e31c5071197
Berger, Yves G., Tirari, Mohammed E.H. and Tille, Yves
(2003)
Towards optimal regression estimation in sample surveys.
Australian & New Zealand Journal of Statistics, 45 (3), .
(doi:10.1111/1467-842X.00286).
Abstract
The Montanari (1987) regression estimator is optimal when the population regression coefficients are known. When the coefficients are estimated, the Montanari estimator is not optimal and can be extremely volatile. Using design-based arguments, this paper proposes a simpler and better alternative to the Montanari estimator that is also optimal when the population regression coefficients are known. Moreover, it can be easily implemented as it involves standard weighted least squares. The estimator is applicable under single stage stratified sampling with unequal probabilities within each stratum.
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Published date: 2003
Keywords:
design-based inference, generalized regression estimator, inclusion probabilities, montanari estimator, conditional poisson sampling
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Local EPrints ID: 34117
URI: http://eprints.soton.ac.uk/id/eprint/34117
ISSN: 1369-1473
PURE UUID: a039d7ed-05a6-467b-a612-ee013e6e072d
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Date deposited: 16 May 2006
Last modified: 16 Mar 2024 03:03
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Author:
Mohammed E.H. Tirari
Author:
Yves Tille
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