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Titlebook: Macroeconomic Forecasting in the Era of Big Data; Theory and Practice Peter Fuleky Book 2020 Springer Nature Switzerland AG 2020 Big Data.M

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書目名稱Macroeconomic Forecasting in the Era of Big Data
副標(biāo)題Theory and Practice
編輯Peter Fuleky
視頻videohttp://file.papertrans.cn/621/620986/620986.mp4
概述Presents a comprehensive collection of big data tools used in macroeconomic forecasting..Surveys the most recent developments in the field..Offers algorithmic descriptions of big data techniques for f
叢書名稱Advanced Studies in Theoretical and Applied Econometrics
圖書封面Titlebook: Macroeconomic Forecasting in the Era of Big Data; Theory and Practice Peter Fuleky Book 2020 Springer Nature Switzerland AG 2020 Big Data.M
描述.This book surveys big data tools used in macroeconomic forecasting and addresses related econometric issues, including how to capture dynamic relationships among variables; how to select parsimonious models; how to deal with model uncertainty, instability, non-stationarity, and mixed frequency data; and how to evaluate forecasts, among others. Each chapter is self-contained with references, and provides solid background information, while also reviewing the latest advances in the field. Accordingly, the book offers a valuable resource for researchers, professional forecasters, and students of quantitative economics..
出版日期Book 2020
關(guān)鍵詞Big Data; Macroeconomic forecasting; Dimension reduction; Shrinkage; Model forecast combination; Dynamic
版次1
doihttps://doi.org/10.1007/978-3-030-31150-6
isbn_softcover978-3-030-31152-0
isbn_ebook978-3-030-31150-6Series ISSN 1570-5811 Series E-ISSN 2214-7977
issn_series 1570-5811
copyrightSpringer Nature Switzerland AG 2020
The information of publication is updating

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https://doi.org/10.1007/978-3-030-31150-6Big Data; Macroeconomic forecasting; Dimension reduction; Shrinkage; Model forecast combination; Dynamic
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Advanced Studies in Theoretical and Applied Econometricshttp://image.papertrans.cn/m/image/620986.jpg
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Dynamic Factor Modelsoven to be indispensable in macroeconomic forecasting. This chapter surveys the evolution of these models from their pre-big-data origins to the large-scale models of recent years. We review the associated estimation theory, forecasting approaches, and several extensions of the basic framework.
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Bootstrap Aggregating and Random Foresting and Decision Trees. In this chapter, we explore Bagging, Random Forest, and their variants in various aspects of theory and practice. We also discuss applications based on these methods in economic forecasting and inference.
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Martin Feldkircher,Florian Huber,Michael Pfarrhofern selbst, der die M?chte des Todes besiegt. Eine signifikante Umdeutung des Odysseus-Mythos erfolgt an der Schwelle zur Neuzeit bei Dante, der die Sicht aus Vergils . übernimmt. In der . ist Odysseus der vom Welthunger getriebene Abenteurer, der Grenzen missachtet, Schiffbruch erleidet und schlie?li
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