On Estimating Finite Mixtures of Multivariate Regression and Simultaneous Equation Models

Abstract

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.

Authors: Kamel Jedidi , Venkat Ramaswamy, Wayne DeSarbo, and Michel Wedel

Format: Journal Article

Publication Date: January 1, 1996

Journal: Structural Equation Modeling

Full Citation

Jedidi, Kamel, Venkat Ramaswamy, Wayne DeSarbo, and Michel Wedel

. “On Estimating Finite Mixtures of Multivariate Regression and Simultaneous Equation Models.”

Structural Equation Modeling

vol.

, (January 01, 1996):

266