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Ideal point discriminant analysis revisited with a special emphasis on visualization. (English) Zbl 1243.62097

Summary: Ideal point discriminant analysis is a classification tool which uses highly intuitive multidimensional scaling procedures. However, Y. Takane wrote about it [Visualization in ideaL in ideal point discriminant analysis. J. Blasius and M.J. Greenacre (eds.), Visualization of Categorical Data, 441–459, NY: Academic Press (1998)]. He concludes that the interpretation is rather intricate and calls that a weakness of the model. We summarize the conditions that provide an easy interpretation and show that in maximum dimensionality they can be obtained without any loss. For reduced dimensionality, it is conjectured that loss is minor which is examined using several data sets.

MSC:

62H30 Classification and discrimination; cluster analysis (statistical aspects)
91C15 One- and multidimensional scaling in the social and behavioral sciences
62P15 Applications of statistics to psychology

Software:

Matlab
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References:

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