86 citations · 187 across the 33 of their papers we have counts for
37 papers
Analytic Standard Errors for Latent Gaussian Discrete-Valued Multivariate Time Series
Christopher M. Crawford, Marie-Christine Düker, Younghoon Kim +3
Unlike their continuous-valued counterparts, there are no universally preferred methodologies for modeling discrete-valued time series. This is especially problematic in fields suc…
Joint modeling and inference of multiple-subject high-dimensional sparse vector autoregressive models
Younghoon Kim, Zachary F. Fisher, Vladas Pipiras
The multiple-subject vector autoregression (multi-VAR) model captures heterogeneous network Granger causality across subjects by decomposing individual sparse VAR transition matric…
Confidence Driven Classification of Application Types in the Presence of Background Network Traffic
Eun Hun Choi, Jasleen Kaur, Vladas Pipiras +2
Accurately classifying the application types of network traffic using deep learning models has recently gained popularity. However, we find that these classifiers do not perform we…
Parametric multi-fidelity Monte Carlo estimation with applications to extremes
Minji Kim, Brendan Brown, Vladas Pipiras
In a multi-fidelity setting, data are available from two sources, high- and low-fidelity. Low-fidelity data has larger size and can be leveraged to make more efficient inference ab…
Penalized Subgrouping of Heterogeneous Time Series
Christopher M. Crawford, Jonathan J. Park, Sy-Miin Chow +3
Interest in the study and analysis of dynamic processes in the social, behavioral, and health sciences has burgeoned in recent years due to the increased availability of intensive…
Testing common structure in high-dimensional factor models: change-point and two-sample procedures
Marie-Christine Düker, Vladas Pipiras
This work proposes a novel procedure to test for common structures across two high-dimensional factor models. The introduced test allows to uncover whether two factor models are dr…