scholarly journals Two-layer EM algorithm for ALD mixture regression models: A new solution to composite quantile regression

2017 ◽  
Vol 115 ◽  
pp. 136-154 ◽  
Author(s):  
Shangshan Wang ◽  
Liming Xiang
Keyword(s):  
Em Algorithm ◽  
Quantile Regression ◽  
Regression Models ◽  
Composite Quantile Regression ◽  
Mixture Regression ◽  
Mixture Regression Models

scholarly journals Modelling semi-continuous data using mixture regression models with an application to cattle production yields

2011 ◽  
Vol 150 (1) ◽  
pp. 109-121 ◽  
Author(s):  
E. J. BELASCO ◽  
S. K. GHOSH
Keyword(s):  
Regression Models ◽  
Continuous Variable ◽  
Continuous Variables ◽  
Multivariate Models ◽  
Mixture Regression ◽  
Potential Applications ◽  
Mixture Regression Models ◽  
Mixture Regression Model ◽  
The Relationship ◽  
Positive Half

SUMMARYThe present paper develops a mixture regression model that allows for distributional flexibility in modelling the likelihood of a semi-continuous outcome that takes on zero value with positive probability while continuous on the positive half of the real line. A multivariate extension is also developed that builds on past multivariate models by systematically capturing the relationship between continuous and semi-continuous variables, while allowing for the semi-continuous variable to be characterized by a mixture model. The flexibility associated with this model provides potential applications in many production system studies. The empirical model is shown to provide a more accurate measure of mortality rates in cattle feedlots, both independently and within a system including other performance and health factors.

scholarly journals Robust fitting of mixture regression models

2012 ◽  
Vol 56 (7) ◽  
pp. 2347-2359 ◽  
Author(s):  
Xiuqin Bai ◽  
Weixin Yao ◽  
John E. Boyer
Keyword(s):  
Regression Models ◽  
Mixture Regression ◽  
Robust Fitting ◽  
Mixture Regression Models
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