Bayesian model clusters, forecasts, and imputes multivariate time series data.
problem Jointly modeling and forecasting sparsely observed multivariate time series with varying dynamics.
method Chinese restaurant process prior for clustering, temporally-reweighted extension for joint modeling within clusters, MCMC for inference.
result Superior forecasting and competitive imputation accuracy compared to baselines, interpretable clusters discovered in macroeconomic data.