Our goal is to create spatio-temporal models for predicting future gubernatorial elections. For a concrete example of how well our models work we use past data to predict the 2018 Arkansas gubernatorial election and use the existing 2018 election data to check our models predictive accuracy. Gubernatorial election data was collected from the Arkansas Secretary of State website while related covariate data was collected from the website for the Federal Reserve Bank of St. Louis. The data we collect is on the county level. For predictive purposes we fit multiple models to the data using Markov chain Monte Carlo and compare each model to determine which has the best predictive ability
Using the index method, we developed the PollyBio model to predict election outcomes. The model, bas...
Ideally, presidential elections should be decided based on how the candidates would handle issues fa...
Population forecasts suggest that the redistribution of the electoral college following Census 2010 ...
This article presents a data-driven Bayesian model used to predict the state-by-state wi...
This paper presents the results of the first a priori test of a gubernatorial election forecast mode...
This bachelor thesis in statistics covers the subject of election forecasting in a multiparty system...
A wide range of potentially useful data are available for election forecasting: the results of previ...
In this paper, it is proposed that voters, devoid of any pressing concerns that could be addressed a...
This paper is a replication and extension of the DeSart and Holbrook presidential election forecast ...
In an increasingly data-driven world, political scientists and statisticians are searching for new m...
The potential for spatial dependence in models of voter turnout, although plausible from a theoretic...
This research examines the time-series geography of voter registrations, presidential elections, sen...
This paper establishes a model to forecast the Presidential election outcomes, particularly the 2016...
Abstract. Traditional election forecasting models are estimated from time-series data on relevant va...
Abstract The primary objective of this research is to obtain an accurate forecasting model for the U...
Using the index method, we developed the PollyBio model to predict election outcomes. The model, bas...
Ideally, presidential elections should be decided based on how the candidates would handle issues fa...
Population forecasts suggest that the redistribution of the electoral college following Census 2010 ...
This article presents a data-driven Bayesian model used to predict the state-by-state wi...
This paper presents the results of the first a priori test of a gubernatorial election forecast mode...
This bachelor thesis in statistics covers the subject of election forecasting in a multiparty system...
A wide range of potentially useful data are available for election forecasting: the results of previ...
In this paper, it is proposed that voters, devoid of any pressing concerns that could be addressed a...
This paper is a replication and extension of the DeSart and Holbrook presidential election forecast ...
In an increasingly data-driven world, political scientists and statisticians are searching for new m...
The potential for spatial dependence in models of voter turnout, although plausible from a theoretic...
This research examines the time-series geography of voter registrations, presidential elections, sen...
This paper establishes a model to forecast the Presidential election outcomes, particularly the 2016...
Abstract. Traditional election forecasting models are estimated from time-series data on relevant va...
Abstract The primary objective of this research is to obtain an accurate forecasting model for the U...
Using the index method, we developed the PollyBio model to predict election outcomes. The model, bas...
Ideally, presidential elections should be decided based on how the candidates would handle issues fa...
Population forecasts suggest that the redistribution of the electoral college following Census 2010 ...