Nowcasting US GDP growth using Machine Learning: a real-time application

Additional Metadata
Keywords	Nowcasting; Real-time; FRED-MD; Random Forest; XGBoost; LSTM neural network; Support Vector Regression; Feature importance; Partial dependence; SHAP values
Thesis Advisor	Pick, A.
Persistent URL	hdl.handle.net/2105/62149
Series	Econometrie
Organisation	Erasmus School of Economics
Citation APA Style AAA Style APA Style Cell Style Chicago Style Harvard Style IEEE Style MLA Style Nature Style Vancouver Style American-Institute-of-Physics Style Council-of-Science-Editors Style BibTex Format Endnote Format RIS Format CSL Format DOIs only Format	Droogh, B.R.M. (2022, February 24). Nowcasting US GDP growth using Machine Learning: a real-time application. Econometrie. Retrieved from http://hdl.handle.net/2105/62149

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