Should we sample a time series more frequently?: decision support via multirate spectrum estimation
High dimensional analysis of time series data and Machine learning problems
Last updated 3rd Jul 2017
CURATOR
Ph.D Candidate, George Mason University
PINBOARD SUMMARY
Network based methodologies for time series that provide new insights into causality and forecasting
High dimensional time series is concerned with data that are characterized by small sample sizes and a large number of features with time trends. As an example, while forecasting the national GDP ...
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