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In this paper we survey the most recent advances in supervised machine learning and highdimensional models for time series forecasting. We consider both linear and nonlinear alternatives. Among the linear methods we pay special attention to penalized regressions and ensemble of models. The...
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Model specification and selection are recurring themes in econometric analysis. Both topics become considerably more complicated in the case of large-dimensional data sets where the set of specification possibilities can become quite large. In the context of linear regression models, penalised...
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our approach bootstrap fails in practice and theory. Instead, we propose a subsampling procedure with automatic parameter …
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regression trees, bagging, random forest, boosting machines and neural networks. Finally, we provide methodologies for analysing …
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