Generalized estimating equations when the response variable has a Tweedie distribution: an application for multi-site rainfall modelling

Swan, Taryn ORCID: https://orcid.org/0000-0002-3564-4354 (2006) Generalized estimating equations when the response variable has a Tweedie distribution: an application for multi-site rainfall modelling. Honours thesis, University of Southern Queensland. (Unpublished)

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Abstract

This dissertation will focus on modelling rainfall processes by using generalized estimating equations, when the assumed distribution of the response variable
is from the Tweedie family of distributions. The Tweedie distribution allows the different components of rainfall to be modelled simultaneously. When the Tweedie distributions are incorporated into generalized estimating equation estimation techniques, not only can the non-independent structure of data be incorporate but also multiple rainfall sites can be modelled concurrently.
This dissertation will attempt to demonstrate the potential benefits of using generalized estimating equations for modelling and interpreting historical
rainfall records by the examination of of monthly rainfall models at Emerald, Toowoomba and Gatton. The suitability and predictability of the models presented in this dissertation will then be discussed to determine
if generalized estimating equations provide a unique method of modelling rainfall.

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Item Type:	Thesis (Non-Research) (Honours)
Item Status:	Live Archive
Additional Information:	Honours thesis. This dissertation was submitted as part of a coursework degree and is not regarded by USQ as a 'Research Thesis'.
Faculty/School / Institute/Centre:	Historic - Faculty of Sciences - Department of Maths and Computing (Up to 30 Jun 2013)
Supervisors:	Dunn, Peter
Date Deposited:	09 May 2008 05:04
Last Modified:	02 Jul 2013 22:52
Uncontrolled Keywords:	modelling rainfall, Tweedie distribution, generalized estimate equation, generalized linear model, multile site modelling
Fields of Research (2008):	01 Mathematical Sciences > 0104 Statistics > 010401 Applied Statistics
Fields of Research (2020):	49 MATHEMATICAL SCIENCES > 4905 Statistics > 490501 Applied statistics
URI:	https://sear.unisq.edu.au/id/eprint/3388

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