Multidimensional Scaling Using the Pseudo-Points Based on Partition Method

Title & Authors
Multidimensional Scaling Using the Pseudo-Points Based on Partition Method
Shin, Sang Min; Kim, Eun-Seong; Choi, Yong-Seok;

Abstract
Multidimensional scaling (MDS) is a graphical technique of multivariate analysis to display dissimilarities among individuals into low-dimensional space. We often have two kinds of MDS which are metric MDS and non-metric MDS. Metric MDS can be applied to quantitative data; however, we need additional information about variables because it only shows relationships among individuals. Gower (1992) proposed a method that can represent variable information using trajectories of the pseudo-points for quantitative variables on the metric MDS space. We will call his method a `replacement method`. However, the trajectory can not be represented even though metric MDS can be applied to binary data when we apply his method to binary data. Therefore, we propose a method to represent information of binary variables using pseudo-points called a `partition method`. The proposed method partitions pseudo-points, accounting both the rate of zeroes and ones. Our metric MDS using the proposed partition method can show the relationship between individuals and variables for binary data.
Keywords
multidimensional scaling;pseudo-points;replacement method;partition method;
Language
Korean
Cited by
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