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AGGREGATION AND ENSEMBLES: PRINCIPLED COMBINATIONS OF DATA
Published online by Cambridge University Press: 04 January 2013
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
- Information
- Copyright
- Copyright © American Political Science Association 2013
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