A Bayesian Vector Multidimensional Scaling Procedure for the Analysis of Ordered Preference Data
分析有序偏好数据的贝叶斯向量多维尺度方法
Multidimensional scaling (MDS) comprises a family of geometric models for the multidimensional representation of data and a corresponding set of methods for fitting such models to actual data. In this paper, we develop a new Bayesian vector MDS model to analyze ordered successive categories preference/dominance data commonly collected in many social science and business studies. A joint spatial representation of the row and column elements of the input data matrix is…