124 citations · 550 across the 52 of their papers we have counts for
7 papers · 1 filter
Optimization and Testing in Linear Non-Gaussian Component Analysis
Ze Jin, Benjamin B. Risk, David S. Matteson
Independent component analysis (ICA) decomposes multivariate data into mutually independent components (ICs). The ICA model is subject to a constraint that at most one of these com…
Interpretable Vector AutoRegressions with Exogenous Time Series
Ines Wilms, Sumanta Basu, Jacob Bien +1
The Vector AutoRegressive (VAR) model is fundamental to the study of multivariate time series. Although VAR models are intensively investigated by many researchers, practitioners o…
Cell Line Classification Using Electric Cell-substrate Impedance Sensing (ECIS)
Megan L. Gelsinger, Laura L. Tupper, David S. Matteson
We consider cell line classification using multivariate time series data obtained from electric cell-substrate impedance sensing (ECIS) technology. The ECIS device, which monitors…
Pruning and Nonparametric Multiple Change Point Detection
Wenyu Zhang, Nicholas James, David Matteson
Change point analysis is a statistical tool to identify homogeneity within time series data. We propose a pruning approach for approximate nonparametric estimation of multiple chan…
Generalizing Distance Covariance to Measure and Test Multivariate Mutual Dependence
Ze Jin, David S. Matteson
We propose three measures of mutual dependence between multiple random vectors. All the measures are zero if and only if the random vectors are mutually independent. The first meas…
Sparse Identification and Estimation of Large-Scale Vector AutoRegressive Moving Averages
Ines Wilms, Sumanta Basu, Jacob Bien +1
The Vector AutoRegressive Moving Average (VARMA) model is fundamental to the theory of multivariate time series; however, identifiability issues have led practitioners to abandon i…