mixture regression models
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Biometrics ◽  
2018 ◽  
Vol 75 (1) ◽  
pp. 183-192 ◽  
Author(s):  
Qiwei Li ◽  
Alberto Cassese ◽  
Michele Guindani ◽  
Marina Vannucci

Author(s):  
Laura A. Gray ◽  
Mónica Hernández Alava

In this article, we describe the betamix command, which fits mixture regression models for dependent variables bounded in an interval. The model is a generalization of the truncated inflated beta regression model introduced in Pereira, Botter, and Sandoval (2012, Communications in Statistics—Theory and Methods 41: 907–919) and the mixture beta regression model in Verkuilen and Smithson (2012, Journal of Educational and Behavioral Statistics 37: 82–113) for variables with truncated supports at either the top or the bottom of the distribution. betamix accepts dependent variables defined in any range that are then transformed to the interval (0, 1) before estimation.


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