Dunn, Peter K. and White, Neil (2005) Power-variance models for modelling rainfall. In: 20th International Workshop on Statistical Modelling, 10 - 15 July 2005, Sydney, Australia.
Modelling rainfall presents difficulties: one is that rainfall is both continuous and discrete. The discrete component corresponds to exactly zero rainfall.
Some researchers circumvent this by using two models - one for determining the
presence and absence of rainfall, another for the rainfall amount. Here, we use
power-variance (Tweedie) generalized linear models, which can explictly model
continuous data with exact zeros. We demonstrate there is a basis for using these
models; that the parameters, in some cases, lend themselves to a useful interpretation; and show the models fit the data well using monthly rainfall data from
Charleville. We then model Australian annual rainfall, and develop a contour
map for the power-variance model index parameter.
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|Item Type:||Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)|
|Item Status:||Live Archive|
|Depositing User:||epEditor USQ|
|Faculty / Department / School:||Historic - Faculty of Sciences - Department of Maths and Computing|
|Date Deposited:||11 Oct 2007 00:28|
|Last Modified:||02 Jul 2013 22:33|
|Uncontrolled Keywords:||Tweedie model, rainfall, generalized linear model, power-variance models.|
|Fields of Research (FoR):||09 Engineering > 0907 Environmental Engineering > 090702 Environmental Engineering Modelling
01 Mathematical Sciences > 0104 Statistics > 010401 Applied Statistics
04 Earth Sciences > 0401 Atmospheric Sciences > 040107 Meteorology
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