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Operational solar forecasting for the real-time market

Yang, Dazhi; Wu, Elynn; Kleissl, Jan - In: International journal of forecasting 35 (2019) 4, pp. 1499-1519

Persistent link: https://www.econbiz.de/10012305380

Measuring uncertainty of a combined forecast and some tests for forecaster heterogeneity

Lahiri, Kajal; Peng, Huaming; Sheng, Xuguang - In: Essays in honor of M. Hashem Pesaran : prediction and …, (pp. 29-50). 2022

Persistent link: https://www.econbiz.de/10013201758

Macroeconomic forecasting using factor models and machine learning : an application to Japan

Maehashi, Kohei; Shintani, Mototsugu - 2020

Persistent link: https://www.econbiz.de/10013329759

Forecasting financial and macroeconomic variables using data reduction methods : new empirical evidence

Kim, Hyun Hak; Swanson, Norman R. - In: Journal of econometrics 178 (2014) 1, pp. 352-367

Persistent link: https://www.econbiz.de/10010256842

Forecasting with many predictors : is boosting a viable alternative?

Buchen, Teresa; Wohlrabe, Klaus - 2010

This paper evaluates the forecast performance of boosting, a variable selection device, and compares it with the … comparison methodology, we find that boosting is a serious competitor for forecasting US industrial production growth in the …

Persistent link: https://www.econbiz.de/10008757436

A boosting approach to forecasting gold and silver returns : economic and statistical forecast evaluation

Pierdzioch, Christian; Risse, Marian; Rohloff, Sebastian - In: Applied economics letters 23 (2016) 4/6, pp. 347-352

Persistent link: https://www.econbiz.de/10011430599

Predicting recessions with leading indicators : model averaging and selection over the business cycle

Berge, Travis J. - In: Journal of forecasting 34 (2015) 6, pp. 455-471

Persistent link: https://www.econbiz.de/10011343630

Predicting recessions with boosted regression trees

Döpke, Jörg; Fritsche, Ulrich; Pierdzioch, Christian - In: International journal of forecasting 33 (2017) 4, pp. 745-759

Persistent link: https://www.econbiz.de/10011746903

Probabilistic time series forecasting with boosted additive models : an application to smart meter data

Ben Taieb, Souhaib; Huser, Raphael; Hyndman, Rob J.; … - 2015

Persistent link: https://www.econbiz.de/10011781252

Predicting recessions in Germany with boosted regression trees

Döpke, Jörg; Fritsche, Ulrich; Pierdzioch, Christian - 2015 - First version: October 2015

We use a machine-learning approach known as Boosted Regression Trees (BRT) to reexamine the usefulness of selected leading indicators for predicting recessions. We estimate the BRT approach on German data and study the relative importance of the indicators and their marginal effects on the...

Persistent link: https://www.econbiz.de/10011381289