Extending the Akaike Information Criterion to Mixture Regression Models

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A review of recent approaches for capturing heterogeneity in partial least squares path modelling (2008, methodology): “Naik et al. (2007) develop a method for the simultaneous determination of the number of segments and variables in finite mixture regression models.”
Finite Mixtures of Generalized Linear Regression Models (2008, methodology): “The performance of newly proposed methods such as a new model selection criterion for mixtures of regression models (Naik et al, 2007) needs for example to be validated in real applications on different empirical data sets.”