A CP low-rank tensor stochastic regression model for time series is proposed with sparse and non-sparse estimators, theoretical error bounds, and applications to macroeconomic and air pollution data.
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Tensor Stochastic Regression for High-dimensional Time Series via CP Decomposition
A CP low-rank tensor stochastic regression model for time series is proposed with sparse and non-sparse estimators, theoretical error bounds, and applications to macroeconomic and air pollution data.