Considering voting rules based on evaluation inputs rather than preference rankings modifies the paradigm of probabilistic studies of voting procedures. This article proposes several simulation models for generating evaluation-based voting inputs. These models can cope with dependent and non identical marginal distributions of the evaluations received by the candidates. A last part is devoted to fitting these models to real data sets.

翻译：基于评价输入而非偏好排序的投票规则改变了投票程序概率研究的范式。本文提出若干生成评价型投票输入的仿真模型，这些模型能够处理候选人所得评价之间具有依赖性且边际分布非恒定的情况。最后一部分专门讨论如何将这些模型拟合至真实数据集。