Archetypal analysis serves as an exploratory tool that interprets a collection of observations as convex combinations of pure (extreme) patterns. When these patterns correspond to actual observations within the sample, they are termed archetypoids. For the first time, we propose applying archetypoid analysis to nominal observations, specifically for identifying archetypal cases from questionnaires featuring nominal multiple-choice questions with a single possible answer. This approach can enhance our understanding of a nominal data set, similar to its application in multivariate contexts. We compare this methodology with the use of archetype analysis and probabilistic archetypal analysis and demonstrate the benefits of this methodology using a real-world example: the German credit dataset.

翻译：典型分析作为一种探索性工具，将一组观测数据解释为纯（极端）模式的凸组合。当这些模式对应于样本中的实际观测值时，它们被称为典型原型。我们首次提出将典型原型分析应用于名义观测数据，特别是用于识别具有单一可能答案的名义多项选择题问卷中的典型个案。这种方法可以增强我们对名义数据集的理解，类似于其在多元背景下的应用。我们将此方法与典型分析及概率典型分析的使用进行比较，并通过一个真实案例——德国信用数据集——展示了该方法的优势。