Abstract
Asymmetric dissimilarity data is observed in various domains such as marketing area. In the situation, Asymmetric Multidimensional Scaling (AMDS) is useful tool to interpret the asymmetric relation between objects visually. However, when the number of objects is large, it becomes to difficult to interpret the relation since these estimated coordinates cannot be interpreted unlike PCA. Here, there are many situations that multivariate data for the same objects of the asymmetric dissimilarity data is given along with the dissimilarity data. Therefore, we try to use the information of the multivariate data to interpret asymmetric relation between objects easily. In this paper, we propose new AMDS such that the estimated coordinates can be interpreted from the path structure like SEM.
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