Complete subset regressions

218 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Forecasting with Factor-Augmented Regression: A Frequentist Model Averaging Approach, Second Version (2013, background): “This paper makes this extension and provides a theoretical justification for frequentist model averaging methods in the presence of estimated factors.”
Forecasting Inflation in a Data-Rich Environment: The Benefits of Machine Learning Methods (2019, methodology): “Notably, Gu et al. (2018) also find that RF, by allowing for nonlinearities, substantially improves stock return predictions.”
Machine Learning Advances for Time Series Forecasting (2020, methodology): “In addition to the models mentioned above, we also include a survey on ensemble-based meth-ods such as Bagging Breiman (1996) and the complete subset regression (CRS, Elliott et al., 2013, 2015).”
Macroeconomic forecast accuracy in a data‐rich environment (2019, unknown): “Our main workhorse is the Regularized Data-Rich Model Averaging (RDRMA), an approach that combines pre-selection and regularization with the Complete Subset Regressions (CSR) of Elliott et al. (2013).”