4 papers
Bayesian inference in high-dimensional models
Sayantan Banerjee, Ismaël Castillo, Subhashis Ghosal
Models with dimension more than the available sample size are now commonly used in various applications. A sensible inference is possible using a lower-dimensional structure. In re…
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…