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Sequential Estimation in Multidimensional Scaling

Published online by Cambridge University Press:  01 January 2025

Hisao Miyano  and
Yukio Inukai
Hisao Miyano*
Affiliation:
Industrial Products Research Institute
Yukio Inukai
Affiliation:
Industrial Products Research Institute
*
Requests for reprints should be sent to Hisao Miyano, Human Factors Engineering Division, Industrial Products Research Institute, 1-1-4 Yatabe-higashi, Tsukuba, Ibaragi, Japan 305.
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Abstract

The concept of sequential estimation is introduced in multidimensional scaling (MDS). The sequential estimation method developed in this paper refers to continually updating estimates of a configuration as new observations are added. This method has a number of advantages, such as a locally optimal design of the experiment can be easily constructed, and dynamic experimentation is made possible. Using artificial data, the performance of our sequential method is illustrated.

Keywords

sequential estimationGauss-Newton methodlocally optimal designInteractive Scaling with Individual Subjects (ISIS)metric multidimensional scaling
Type
Original Paper
Information
Psychometrika , Volume 47 , Issue 3 , September 1982 , pp. 321 - 336
Copyright
Copyright © 1982 The Psychometric Society

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Footnotes

We are indebted to anonymous reviewers for their suggestions. In addition, we thank Dr. Frank Critchley for his helpful comments on our Q/S algorithm.

References

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