363 citations · 989 across the 32 of their papers we have counts for
5 papers · 1 filter
Estimating the error variance in a high-dimensional linear model
Guo Yu, Jacob Bien
The lasso has been studied extensively as a tool for estimating the coefficient vector in the high-dimensional linear model; however, considerably less is known about estimating th…
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…
Valid Inference Corrected for Outlier Removal
Shuxiao Chen, Jacob Bien
Ordinary least square (OLS) estimation of a linear regression model is well-known to be highly sensitive to outliers. It is common practice to (1) identify and remove outliers by l…
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…
BigVAR: Tools for Modeling Sparse High-Dimensional Multivariate Time Series
William Nicholson, David Matteson, Jacob Bien
The R package BigVAR allows for the simultaneous estimation of high-dimensional time series by applying structured penalties to the conventional vector autoregression (VAR) and vec…