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arXiv 0901.4203stat.APstat.CO
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秩数据的混合专家模型及其在选举研究中的应用

A mixture of experts model for rank data with applications in election studies

Isobel Claire Gormley, Thomas Brendan Murphy

摘要:

投票集团被定义为具有相似投票偏好的一组选民。爱尔兰选民分裂成投票集团是一个有趣的现象。爱尔兰的选举采用"单一可转移投票“选举制度;在这一制度下,选民按照偏好对部分或全部候选人进行排序。这些等级投票提供了丰富的偏好信息来源,可以从中推断选民的组成。此外,社会因素或协变量对选民构成的影响也很有趣。混合专家模型是一种混合模型,其中模型参数是协变量的函数。混合专家模型的排名数据提供了一个基于模型的方法来聚类爱尔兰选民到投票集团,研究社会因素对这种聚类的影响,并检查投票集团的特征偏好。秩数据的Benter模型被用作专家混合模型中的组分密度族;广义线性模型理论被用来模拟协变量对混合比例的影响。通过EM和MM算法的混合实现模型拟合。的方法的一个例子是说明通过检查爱尔兰总统选举。选民中存在投票集团,并确定年龄和政府满意度是影响这次选举投票的重要因素。

英文摘要:

A voting bloc is defined to be a group of voters who have similar voting preferences. The cleavage of the Irish electorate into voting blocs is of interest. Irish elections employ a ``single transferable vote'' electoral system; under this system voters rank some or all of the electoral candidates in order of preference. These rank votes provide a rich source of preference information from which inferences about the composition of the electorate may be drawn. Additionally, the influence of social factors or covariates on the electorate composition is of interest. A mixture of experts model is a mixture model in which the model parameters are functions of covariates. A mixture of experts model for rank data is developed to provide a model-based method to cluster Irish voters into voting blocs, to examine the influence of social factors on this clustering and to examine the characteristic preferences of the voting blocs. The Benter model for rank data is employed as the family of component densities within the mixture of experts model; generalized linear model theory is employed to model the influence of covariates on the mixing proportions. Model fitting is achieved via a hybrid of the EM and MM algorithms. An example of the methodology is illustrated by examining an Irish presidential election. The existence of voting blocs in the electorate is established and it is determined that age and government satisfaction levels are important factors in influencing voting in this election.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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