Subedi, Sanjeena; Punzo, Antonio; Ingrassia, Salvatore; … - In: Advances in Data Analysis and Classification 7 (2013) 1, pp. 5-40
In model-based clustering and classification, the cluster-weighted model is a convenient approach when the random vector of interest is constituted by a response variable <InlineEquation ID="IEq1"> <EquationSource Format="TEX">$$Y$$</EquationSource> </InlineEquation> and by a vector <InlineEquation ID="IEq2"> <EquationSource Format="TEX">$${\varvec{X}}$$</EquationSource> </InlineEquation> of <InlineEquation ID="IEq3"> <EquationSource Format="TEX">$$p$$</EquationSource> </InlineEquation> covariates. However, its applicability may be limited when <InlineEquation ID="IEq4"> <EquationSource Format="TEX">$$p$$</EquationSource> </InlineEquation> is...</equationsource></inlineequation></equationsource></inlineequation></equationsource></inlineequation></equationsource></inlineequation>
