activity
20082023
most citedSmoothing and mean-covariance estimation of functional data with a Bayesian hierarchical model

49 citations · 90 across the 5 of their papers we have counts for

collaborators

5 papers

stat.AP2023

Predicting COVID-19 hospitalisation using a mixture of Bayesian predictive syntheses

Genya Kobayashi, Shonosuke Sugasawa, Yuki Kawakubo +2

This paper proposes a novel methodology called the mixture of Bayesian predictive syntheses (MBPS) for multiple time series count data for the challenging task of predicting the nu…

stat.ME2020

Use of Cross-validation Bayes Factors to Test Equality of Two Densities

Jeffery Hart, Taeryon Choi, Naveed Merchant

We propose a non-parametric, two-sample Bayesian test for checking whether or not two data sets share a common distribution. The test makes use of data splitting ideas and does not…

stat.ME2015★ 2 cited

Efficient Bayesian hierarchical functional data analysis with basis function approximations using Gaussian-Wishart processes

Jingjing Yang, Dennis D. Cox, Jong Soo Lee +2

Functional data are defined as realizations of random functions (mostly smooth functions) varying over a continuum, which are usually collected with measurement errors on discretiz…

stat.ME2014★ 49 cited

Smoothing and mean-covariance estimation of functional data with a Bayesian hierarchical model

Jingjing Yang, Hongxiao Zhu, Taeryon Choi +1

Functional data, with basic observational units being functions (e.g., curves, surfaces) varying over a continuum, are frequently encountered in various applications. While many st…

math.ST2008★ 39 cited

Remarks on consistency of posterior distributions

Taeryon Choi, R. V. Ramamoorthi

In recent years, the literature in the area of Bayesian asymptotics has been rapidly growing. It is increasingly important to understand the concept of posterior consistency and va…