Regression for compositional data by using distributions defined on the hypersphere
Compositional data can be transformed to directional data by the square-root transformation and then modelled by using distributions defined on the hypersphere. One advantage of this approach is that zero components are catered for naturally in the models. The Kent distribution for directional data is a good candidate model because it has a sufficiently general covariance structure. We propose a new regression model which models the mean direction of the Kent distribution as a function of a...[Show more]
|Collections||ANU Research Publications|
|Source:||Journal of the Royal Statistical Society Series B|
|01_Scealy_Regression_for_compositional_2011.pdf||814.01 kB||Adobe PDF||Request a copy|
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