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AGGREGATION AND ENSEMBLES: PRINCIPLED COMBINATIONS OF DATA

Published online by Cambridge University Press:  04 January 2013

Jacob M. Montgomery
Affiliation:
Washington University, St. Louis
Florian M. Hollenbach
Affiliation:
Duke University
Michael D. Ward
Affiliation:
Duke University

Extract

Perhaps the major story in forecasting the 2012 election is the growing awareness of the benefits of aggregating multiple sources of data for improving prediction. Most prominently, polling analysts including Simon Jackman, Drew Linzer, and Nate Silver made the strong case, ultimately validated by the election results, that combining information from multiple polls gives a better picture of the electorate than any poll analyzed in isolation.

Type
Features Symposium: Recap: Forecasting the 2012 Election
Copyright
Copyright © American Political Science Association 2013

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References

Montgomery, J.M., Hollenbach, F.M., and Ward, M.D.. 2012a. “Ensemble Predictions of the 2012 US Presidential Election,PS: Political Science and Politics 45 (4): 651–54.Google Scholar
Montgomery, J.M., Hollenbach, F.M., and Ward, M.D.. 2012b. “Say Yes to the Guess: Tailoring Elegant Ensembles on a Tight (Data) Budget,” Annual Meeting of the American Political Science Association, New Orleans, LA.Google Scholar