LADI: A Latent Discriminant Model for Analyzing Marketing Research Data
作者提出了一种名为LADI的潜在判别模型，用于分析市场研究数据。该模型是一种基于模型的聚类方法，其核心思想是将判别问题置于潜在混合模型的框架中。通过最大似然估计，模型可以估计混合参数和结构参数，从而根据一组描述变量的响应来定义潜在聚类。LADI模型的特点包括：能够处理不同尺度类型的描述变量、允许探索群体结构、提供统计检验以确定保留的潜在聚类数量，以及允许对解施加约束。该模型为市场研究中的聚类分析提供了一种灵活且通用的工具。
A general, flexible LAtent DIscriminant model is described. LADI is a model-based clustering procedure, derived from a specific conceptualization in which the discrimination problem is viewed in a latent mixture context. The basic model yields maximum likelihood (ML) estimates of mixing parameters and structural parameters that define the latent clusters in terms of the responses to a set of descriptor variables. Among other features, the model accommodates descriptor variables having different scale properties, allows for the investigation of group structure, provides a statistical test of the number of latent clusters to retain, and allows for constraints to be imposed on the solution.