Modelling techniques for compositional data using distributions defined on the hypersphere
Compositional data can be transformed to directional data by the square root transformation and then modelled using distributions defined on the hypersphere. The purpose of this thesis is to investigate new modelling techniques for a general p-dimensional compositional data vector using this square root transformation approach. One advantage 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...[Show more]
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