A New Semiparametric Approach to Finite Mixture of Regressions using Penalized Regression via Fusion
Erin E. Austin, Wei Pan, Xiaotong T. Shen · Statistica Sinica · 2018
penalty that shrinks the differences between estimated parameter vectors. The methodology causes the individuals' models to cluster into a few common models, in turn revealing previously unknown subpopulations. In fact, by varying the penalty strength, the new method can reveal a hierarchical structure among the subpopulations that can be useful in exploratory analyses. Simulations using FMR models and a real-data analysis show that the method performs promisingly well.