198 citations · 888 across the 47 of their papers we have counts for
17 papers · 1 filter
Bayesian Graphical High-Dimensional Time Series Models for Detecting Structural Changes
Shuvrarghya Ghosh, Arkaprava Roy, Anindya Roy +1
We study the structural changes in multivariate time-series by estimating and comparing stationary graphs for macroeconomic time series before and after an economic crisis such as…
Bayesian Inference for High-dimensional Time Series with a Stationary Directed Acyclic Graphical Structure
Arkaprava Roy, Anindya Roy, Subhashis Ghosal
In multivariate time series analysis, understanding the underlying causal relationships among variables is often of interest for various applications. Directed acyclic graphs (DAGs…
Relational Graph in Vector Autoregression: A Case Study on the Effect of the Great Recession on Connectivity of Economic Indicators
Arkaprava Roy, Anindya Roy, Subhashis Ghosal
Under a high-dimensional vector autoregressive (VAR) model, we propose a way of efficiently estimating both the stationary graph structure between the nodal time series and their t…
Coverage of Credible Sets for Regression under Variable Selection
Samhita Pal, Subhashis Ghosal
We study the asymptotic frequentist coverage of credible sets based on a novel Bayesian approach for a multiple linear regression model under variable selection. We initially ignor…
Bayesian Learning of Relational Graph in Semiparametric High-dimensional Time Series
Arkaprava Roy, Anindya Roy, Subhashis Ghosal
Time series data arising in many applications nowadays are high-dimensional. A large number of parameters describe features of these time series. We propose a novel approach to mod…
Bayesian Multivariate Quantile Regression Using Dependent Dirichlet Process Prior
Indrabati Bhattacharya, Subhashis Ghosal
In this article, we consider a non-parametric Bayesian approach to multivariate quantile regression. The collection of related conditional distributions of a response vector Y give…