Towards optimal regression estimation in sample surveys


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), 319-329. (doi:10.1111/1467-842X.00286).

Download

Full text not available from this repository.

Original Publication URL: http://dx.doi.org/10.1111/1467-842X.00286

Description/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.

Item Type: Article
ISSNs: 1369-1473 (print)
Related URLs:
Keywords: design-based inference, generalized regression estimator, inclusion probabilities, montanari estimator, conditional poisson sampling
Subjects: H Social Sciences > HA Statistics
Divisions: University Structure - Pre August 2011 > Southampton Statistical Sciences Research Institute
ePrint ID: 34117
Date Deposited: 16 May 2006
Last Modified: 27 Mar 2014 18:21
URI: http://eprints.soton.ac.uk/id/eprint/34117

Actions (login required)

View Item View Item