Morris, Katherine; McNicholas, Paul; Scrucca, Luca - In: Advances in Data Analysis and Classification 7 (2013) 3, pp. 321-338
We introduce a dimension reduction method for model-based clustering obtained from a finite mixture of <InlineEquation ID="IEq3"> <EquationSource Format="TEX">$$t$$</EquationSource> <EquationSource Format="MATHML"> <math xmlns:xlink="http://www.w3.org/1999/xlink"> <mrow> <mi>t</mi> </mrow> </math> </EquationSource> </InlineEquation>-distributions. This approach is based on existing work on reducing dimensionality in the case of finite Gaussian mixtures. The method relies on identifying a reduced subspace of...</equationsource></equationsource></inlineequation>
