Bayesian Computation via the Gibbs Sampler for Mixture Models with Gaussian Distal Outcomes

2021 ◽  
pp. 1-12
Author(s):  
Lilia C. C. da Costa ◽  
Leila D. A. F. Amorim ◽  
Gilmara S. Bispo
Keyword(s):  
Mixture Models ◽  
Gibbs Sampler ◽  
Bayesian Computation

Modeling the crashes count using finite mixture models

2019 ◽  
Vol 7 (1) ◽  
pp. 13-27
Author(s):  
Safaa K. Kadhem ◽  
Sadeq A. Kadhim
Keyword(s):  
Bayesian Inference ◽  
Mixture Models ◽  
Gibbs Sampler ◽  
Simulation Study ◽  
Finite Mixture Models ◽  
Synthetic Data ◽  
Finite Mixture Model ◽  
Finite Mixture ◽  
Model Parameters ◽  
Mcmc Method

"This paper aims at the modeling the crashes count in Al Muthanna governance using finite mixture model. We use one of the most common MCMC method which is called the Gibbs sampler to implement the Bayesian inference for estimating the model parameters. We perform a simulation study, based on synthetic data, to check the ability of the sampler to find the best estimates of the model. We use the two well-known criteria, which are the AIC and BIC, to determine the best model fitted to the data. Finally, we apply our sampler to model the crashes count in Al Muthanna governance.

scholarly journals A blocked Gibbs sampler for NGG-mixture models via a priori truncation

2015 ◽  
Vol 26 (3) ◽  
pp. 641-661 ◽  
Author(s):  
Raffaele Argiento ◽  
Ilaria Bianchini ◽  
Alessandra Guglielmi
Keyword(s):  
Mixture Models ◽  
Gibbs Sampler ◽  
A Priori

Post Hoc Investigation of Factor Mixture Models

2007 ◽  
Author(s):  
Danielle L. Cisler ◽  
Gitta H. Lubke
Keyword(s):  
Mixture Models ◽  
Post Hoc
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