6 papers
A Bayesian Bi-Directional Splitting Framework for Variable Selection in Large Datasets
Aaron Coats, Vinny Davies, Mayetri Gupta
Modern tabular datasets are becoming increasingly large, both in the number of samples and covariates, posing significant challenges for Bayesian variable selection due to the resu…
ZINBGT: Exploratory Data Analysis of Single-Cell Transcriptomic Expression Using Mixture Models
Toby Kettlewell, Yiyi Cheng, Thomas D. Otto +2
Single-cell transcriptomic data approximates the abundance of proteins at a high resolution, but its noisiness necessitates transformation by a pipeline of methods before analysis…
On the identifiability of Dirichlet mixture models
Hien Duy Nguyen, Mayetri Gupta
We study identifiability of finite mixtures of Dirichlet distributions on the interior of the simplex. We first prove a shift identity showing that every Dirichlet density can be w…
On the large-sample limits of some Bayesian model evaluation statistics
Hien Duy Nguyen, Mayetri Gupta, Jacob Westerhout +1
Model selection and order selection problems frequently arise in statistical practice. A popular approach to addressing these problems in the frequentist setting involves informati…
Finite sample inference for empirical Bayesian methods
Hien D Nguyen, Mayetri Gupta
In recent years, empirical Bayesian (EB) inference has become an attractive approach for estimation in parametric models arising in a variety of real-life problems, especially in c…
Model selection and sensitivity analysis for sequence pattern models
Mayetri Gupta
In this article we propose a maximal a posteriori (MAP) criterion for model selection in the motif discovery problem and investigate conditions under which the MAP asymptotically g…