scholarly journals Functional Finite Mixture Regression Models

2024 ◽  
Author(s):  
Xiao Wang ◽  
Yufeng Liu ◽  
Hongtu Zhu
2011 ◽  
Vol 150 (1) ◽  
pp. 109-121 ◽  
Author(s):  
E. J. BELASCO ◽  
S. K. GHOSH

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.


2018 ◽  
Vol 32 (6) ◽  
pp. 1509-1560 ◽  
Author(s):  
Jian Liang ◽  
Kun Chen ◽  
Ming Lin ◽  
Changshui Zhang ◽  
Fei Wang

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