A Bayesian basket trial design using a calibrated Bayesian hierarchical model

Predicting waste generation using Bayesian model averaging

A prognosis model has been developed for solid waste generation from households in Hoi An City, a famous tourist city in Viet Nam. Waste sampling, followed by a questionnaire survey, was carried out to gather data. The Bayesian model average method was used to identify factors significantly associated with waste generation. Multivariate linear regression analysis was then applied to evaluate th...

Inferring regulatory networks using a hierarchical Bayesian graphical Gaussian model

In this paper, we propose a new formalism based on graphical Gaussian model (GGM) to infer genetic regulatory networks. A hierarchical Bayesian prior for the precision matrix of the GGM is introduced to impose a bias toward sparse graph structure. We show that the MAP estimation of the undirected graph can be readily obtained by a variant of the well-known Lasso regression algorithm. Then we in...

Gene selection using a two-level hierarchical Bayesian model

SUMMARY The fundamental problem of gene selection via cDNA data is to identify which genes are differentially expressed across different kinds of tissue samples (e.g. normal and cancer). cDNA data contain large number of variables (genes) and usually the sample size is relatively small so the selection process can be unstable. Therefore, models which incorporate sparsity in terms of variables (...

Defining and Testing Diagnostic Equivalence Using a Bayesian Hierarchical Model

Improving Face Recognition Performance Using a Hierarchical Bayesian Model

Over the past two decades, face recognition research has shot to the forefront due to its increased demand in security and commercial applications. Many facial feature extraction techniques for the purpose of recognition have been developed, some of which have also been successfully installed and used. Principal Component Analysis (PCA), also popularly called as Eigenfaces has been used success...