An Expectation-Maximization (EM) algorithm in a maximum likelihood framework is developed to estimate finite mixtures of multivariate regression and simultaneous equation models with multiple endogenous variables. A dataset with cross-sectional observations for a diverse sample of businesses illustrates the semiparametric approach.
Jedidi, Kamel, Venkat Ramaswamy, Wayne DeSarbo, and Michel Wedel. "On Estimating Finite Mixtures of Multivariate Regression and Simultaneous Equation Models." Structural Equation Modeling 3 (1996): 266-89.
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