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Modeling High-Dimensional Dependent Data in the Presence of Many Explanatory Variables and Weak Signals
This article considers a novel and widely applicable approach to modeling high-dimensional dependent data when a large number of explanatory variables are available and the signal-to-noise ratio is low. We postulate that a $p$-dimensional response series is the sum of a linear regression with many observable explanatory variables and an …