3 papers
stat.ME2025
Efficient Bayesian inference for two-stage models in environmental epidemiology
Konstantin Larin, Daniel R. Kowal
Statistical models often require inputs that are not completely known. This can occur when inputs are measured with error, indirectly, or when they are predicted using another mode…
stat.ME2025
A dynamic copula model for probabilistic forecasting of non-Gaussian multivariate time series
John Zito, Daniel R. Kowal
Multivariate time series (MTS) data often include a heterogeneous mix of non-Gaussian distributional features (asymmetry, multimodality, heavy tails) and data types (continuous and…
stat.ME2024
Bayesian Functional Graphical Models with Change-Point Detection
Chunshan Liu, Daniel R. Kowal, James Doss-Gollin +1
Functional data analysis, which models data as realizations of random functions over a continuum, has emerged as a useful tool for time series data. Often, the goal is to infer the…