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A Markov chain Monte Carlo (MCMC) methodology withbootstrap percentile estimates for predicting presidential election results in Ghana

机译：马尔可夫链蒙特卡罗（MCMC）方法论引导百分位估计以预测加纳总统选举结果

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Although, there exists numerous literature on the procedure for forecasting or predicting election results, in Ghana only opinion poll strategies have been used. To fill this gap, the paper develops Markov chain models for forecasting the 2016 presidential election results at the Regional, Zonal (i.e. Savannah, Coastal and Forest) and the National levels using past presidential election results of Ghana. The methodology develops a model for prediction of the 2016 presidential election results in Ghana using the Markov chains Monte Carlo (MCMC) methodology with bootstrap estimates. The results were that the ruling NDC may marginally win the 2016 Presidential Elections but would not obtain the more than 50 % votes to be declared an outright winner. This means that there is going to be a run-off election between the two giant political parties: the ruling NDC and the major opposition party, NPP. The prediction for the 2016 Presidential run-off election between the NDC and the NPP was rather in favour of the major opposition party, the NPP with a little over the 50 % votes obtained.
机译：尽管有大量关于预测或预测选举结果的程序的文献，但在加纳，仅使用了民意测验策略。为了填补这一空白，本文开发了马尔可夫链模型，以使用加纳以往的总统选举结果来预测2016年区域，分区（即萨凡纳，沿海和森林）和国家一级的总统选举结果。该方法论使用马尔可夫链蒙特卡洛（MCMC）方法论与自举法估计数，开发了一个预测2016年加纳总统选举结果的模型。结果是执政的NDC可能会在2016年总统大选中获胜，但不会获得超过50％的选票被宣布为直接赢家。这意味着，两个大政党将在即将举行的选举中进行选举：执政的国家民主党和主要反对党国家党。 NDC和NPP之间2016年总统大选的预测相当赞成主要反对党，NPP的选票略高于50％。

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