Dynamic Bayesian Forecasting of Presidential Elections in the States

DOI10.1080/01621459.2012.737735OpenAlexW2162797709MaRDI QIDQ4916933

Drew A. Linzer

Publication date: 26 April 2013

Published in: Journal of the American Statistical Association (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/01621459.2012.737735

zbMATH Keywords

votingpoliticspublic opinionpolls

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (8)

Preelectoral polls variability: a hierarchical Bayesian model to assess the role of house effects with application to Italian elections ⋮ Postelection analysis of presidential election/poll data ⋮ Bayesian hierarchical stacking: some models are (somewhere) useful ⋮ Hierarchical model for forecasting the outcomes of binary referenda ⋮ Forecasting Elections Using Compartmental Models of Infection ⋮ Dynamic Bayesian influenza forecasting in the United States with hierarchical discrepancy (with discussion) ⋮ Predicting competitions by combining conditional logistic regression and subjective Bayes: an Academy Awards case study ⋮ Tracking the Impact of Media on Voter Choice in Real Time: A Bayesian Dynamic Joint Model

Uses Software

• Unnamed Item

Cites Work

• Inference from iterative simulation using multiple sequences
• A New Approach to Estimating the Probability of Winning the Presidency

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