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Bayesian analysis for categorical survey data

Grapsa, Erofili (2010) Bayesian analysis for categorical survey data University of Southampton, Mathematics: Statistics, Doctoral Thesis , 152pp.

Record type: Thesis (Doctoral)

Abstract

In this thesis, we develop Bayesian methodology for univariate and multivariate categorical survey data. The Multinomial model is used and the following problems are addressed. Limited information about the design variables leads us to model the unknown design variables taking into account the sampling scheme. Random effects are incorporated in the model to deal with the effect of sampling design, that produces the Multinomial GLMM and issues such as model comparison and model averaging are also discussed. The methodology is applied in a true dataset and estimates for population counts are obtained

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More information

Published date: 1 December 2010
Organisations: University of Southampton, Statistics

Identifiers

Local EPrints ID: 197303
URI: http://eprints.soton.ac.uk/id/eprint/197303
PURE UUID: be6d2b39-500d-42b8-9a98-ff04282805f8

Catalogue record

Date deposited: 21 Sep 2011 10:38
Last modified: 18 Jul 2017 11:20

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Contributors

Author: Erofili Grapsa
Thesis advisor: Jonathan Forster

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