Bayesian Mixture Model for Prediction of Bus Arrival Time

2015 ◽  
Vol 6 (6) ◽  
pp. 961
Author(s):  
Misbahuddin Misbahuddin ◽  
Riri Fitri Sari
Keyword(s):  
Mixture Model ◽  
Arrival Time ◽  
Bayesian Mixture Model ◽  
Bayesian Mixture

scholarly journals Bayesian Mixture Model Analysis for Detecting Differentially Expressed Genes

2008 ◽  
Vol 2008 ◽  
pp. 1-12 ◽  
Author(s):  
Zhenyu Jia ◽  
Shizhong Xu
Keyword(s):  
Mixture Model ◽  
Differentially Expressed Genes ◽  
Differential Expression Analysis ◽  
Differentially Expressed ◽  
Control Treatment ◽  
Microarray Gene Expression ◽  
Bayesian Mixture Model ◽  
Bayesian Mixture ◽  
Truncated Normal ◽  
Upregulated Genes

Control-treatment design is widely used in microarray gene expression experiments. The purpose of such a design is to detect genes that express differentially between the control and the treatment. Many statistical procedures have been developed to detect differentially expressed genes, but all have pros and cons and room is still open for improvement. In this study, we propose a Bayesian mixture model approach to classifying genes into one of three clusters, corresponding to clusters of downregulated, neutral, and upregulated genes, respectively. The Bayesian method is implemented via the Markov chain Monte Carlo (MCMC) algorithm. The cluster means of down- and upregulated genes are sampled from truncated normal distributions whereas the cluster mean of the neutral genes is set to zero. Using simulated data as well as data from a real microarray experiment, we demonstrate that the new method outperforms all methods commonly used in differential expression analysis.

A Bayesian mixture model for clustering circular data

2020 ◽  
Vol 143 ◽  
pp. 106842
Author(s):  
Carlos E. Rodríguez ◽  
Gabriel Núñez-Antonio ◽  
Gabriel Escarela
Keyword(s):  
Mixture Model ◽  
Circular Data ◽  
Bayesian Mixture Model ◽  
Bayesian Mixture
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