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-- Part II. The status of machine learning methods for time series and new products forecasting -- 3. Forecasting with … Forecasting -- Part III. Global forecasting models -- 5. Forecasting in Big Data with Global Forecasting Models -- 6. How to … leverage data for Time Series Forecasting with Artificial Intelligence models: Illustrations and Guidelines for Cross …
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data sampling (MIDAS) regression is mainly a forecasting tool designed to harness mixed-frequency data. This dissertation … supervise banks inconsistently which affects the formation of costs. The accuracy of forecasting is low for banks supervised by … and it is discovered that the MIDAS model has superior forecasting accuracy as compared to the HAR model. The economic …
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services: trends, challenges, and empirical evidence from Germany -- Forecasting and Planning with Auxiliary Data During a … management, forecasting, and business analytics undertaken by firms and institutions to quickly adapt their supply chains to …
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Since the advent of Markov chain Monte Carlo (MCMC) methods in the early 1990s, Bayesian methods have been proposed for a large and growing number of applications. One of the main advantages of Bayesian inference is the ability to deal with many different sources of uncertainty, including data,...
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This book highlights research on the behavioral biases affecting judgmental accuracy in judgmental forecasting and … possible to use predictive analytics to exploit highly complex (big) data resources. Consequently, modern forecasting … that in the majority of industry contexts, human judgment remains an indispensable component of the managerial forecasting …
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from the ifo Business Survey have proved to be indispensable for business cycle analysis and economic forecasting. In …
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