Bayesian Semiparametric Local Clustering of Multiple Time Series Data

In multiple time series data, clustering the component profiles can identify meaningful latent groups while also detecting interesting change points in their trajectories. Conventional time series …

Bayesian Nonparametric Common Atoms Regression for Generating Synthetic Contr…

The availability of electronic health records (EHR) has opened opportunities to supplement increasingly expensive and difficult to carry out randomized controlled trials (RCT) with evidence from re…

Bayesian Semiparametric Covariate Informed Multivariate Density Deconvolution

Estimating the marginal and joint densities of the long-term average intakes of different dietary components is an important problem in nutritional epidemiology. Since these variables cannot be dir…

Bayesian Semiparametric Longitudinal Drift-Diffusion Mixed Models for Tone Le…

Understanding how adult humans learn nonnative speech categories such as tone information has shed novel insights into the mechanisms underlying experience-dependent brain plasticity. Scientists ha…

Bayesian Copula Density Deconvolution for Zero-Inflated Data in Nutritional E…

Estimating the marginal and joint densities of the long-term average intakes of different dietary components is an important problem in nutritional epidemiology. Since these variables cannot be dir…

A Powerful Bayesian Test for Equality of Means in High Dimensions

Bayesian Semiparametric Mixed Effects Markov Models With Application to Vocal…

Bayesian Semiparametric Multivariate Density Deconvolution

Bayesian Nonparametric Modeling of Higher Order Markov Chains