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Sequential estimation in multidimensional scaling

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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.

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Authors and Affiliations

  1. Human Factors Engineering Division, Industrial Products Research Institute, 1-1-4 Yatabe-higashi, Tsukuba, 305, Ibaragi, Japan

    Hisao Miyano & Yukio Inukai

Authors
  1. Hisao Miyano
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  2. Yukio Inukai
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Additional information

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.

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Miyano, H., Inukai, Y. Sequential estimation in multidimensional scaling. Psychometrika 47, 321–336 (1982). https://doi.org/10.1007/BF02294163

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  • DOI: https://doi.org/10.1007/BF02294163

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