Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.703458
Title: Multivariate structure preserving estimation for population compositions
Author: Luna Hernandez, Angela
ISNI:       0000 0004 6061 7977
Awarding Body: University of Southampton
Current Institution: University of Southampton
Date of Award: 2016
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Abstract:
This document introduces a new Structure Preserving Estimator for Small Area compositions, using data from a proxy and a sample compositions. The proposed estimator, the Multivariate Structure Preserving Estimator (MSPREE), extends the two main SPREE-type estimators: the SPREE and the GSPREE. The additional flexibility of the MSPREE may lead to estimates with less MSE than its predecessors. An extension of the MSPREE including cell specific random effects, the Mixed MSPREE (MMSPREE), is also presented, in an attempt to further reduce the size of the bias when the associated sample size allows for it. In order to estimate the variance components governing the variance structure of the random effects in the MMSPREE, an unbiased moment-type estimator is proposed. Furthermore, an estimator for the variance of the MSPREE, as well as methodologies to evaluate the unconditional and finite population MSE of both MSPREE and MMSPREE, are developed. The behaviour of the proposed estimators is illustrated in a controlled setting via a simulation exercise, and in a real data application.
Supervisor: Tzavidis, Nikolaos ; Zhang, Li Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.703458  DOI: Not available
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