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Machine Learning Advances for Time Series Forecasting
In this paper we survey the most recent advances in supervised machine learning and high-dimensional models for time series forecasting.
Do We Exploit all Information for Counterfactual Analysis? Benefits of Factor Models and Idiosyncratic Correction
The data consist of daily sales and prices of five different products over more than 400 municipalities.
Regularized Estimation of High-Dimensional Vector AutoRegressions with Weakly Dependent Innovations
There has been considerable advance in understanding the properties of sparse regularization procedures in high-dimensional models.
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