Variable Selection in Heteroscedastic Regression Models Under General Skew-t Distributional Models Using Information Complexity

2020 ◽  
pp. 73-98
Author(s):  
Yeşim Güney ◽  
Olcay Arslan ◽  
Hamparsum Bozdogan
Keyword(s):  
Variable Selection ◽  
Regression Models ◽  
Information Complexity ◽  
Heteroscedastic Regression

scholarly journals Correction to: MicroBVS: Dirichlet-tree multinomial regression models with Bayesian variable selection - an R package

2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Matthew D. Koslovsky ◽  
Marina Vannucci
Keyword(s):  
Variable Selection ◽  
Regression Models ◽  
R Package ◽  
Bayesian Variable Selection ◽  
Multinomial Regression

An amendment to this paper has been published and can be accessed via the original article.

Scalable Bayesian variable selection regression models for count data

2020 ◽  
pp. 187-219 ◽  
Author(s):  
Yinsen Miao ◽  
Jeong Hwan Kook ◽  
Yadong Lu ◽  
Michele Guindani ◽  
Marina Vannucci
Keyword(s):  
Variable Selection ◽  
Count Data ◽  
Regression Models ◽  
Bayesian Variable Selection

Some results for robust GM-based estimators in heteroscedastic regression models

2000 ◽  
Vol 89 (1-2) ◽  
pp. 215-242 ◽  
Author(s):  
Ana Bianco ◽  
Graciela Boente ◽  
Julio di Rienzo
Keyword(s):  
Regression Models ◽  
Heteroscedastic Regression
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