A Selective Overview and Comparison of Robust Mixture Regression Estimators

Volume: 88, Issue: 1, Pages: 176 - 202
Published: Nov 29, 2019
Abstract
Summary Mixture regression models have been widely used in business, marketing and social sciences to model mixed regression relationships arising from a clustered and thus heterogeneous population. The unknown mixture regression parameters are usually estimated by maximum likelihood estimators using the expectation–maximisation algorithm based on the normality assumption of component error density. However, it is well known that the...
Paper Details
Title
A Selective Overview and Comparison of Robust Mixture Regression Estimators
Published Date
Nov 29, 2019
Volume
88
Issue
1
Pages
176 - 202
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