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Autor(en): 
  • Shizuhiko Nishisato
  • Optimal Quantification and Symmetry 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   i.d.R. innert 7-14 Tagen versandfertig
    Veröffentlichung:  Februar 2022  
    Genre:  Schulbücher 
     
    correspondenceanalysis / Datenbanken / Datenmanagement / DualScaling / mathematicalsymmetry / MultidimensionalNonlinearAnalysis / OptimalAnalysisofQualitativeData / Quantificationanalysis / SpatialSymmetry
    ISBN:  9789811691690 
    EAN-Code: 
    9789811691690 
    Verlag:  Springer 
    Einband:  Gebunden  
    Sprache:  English  
    Dimensionen:  H 241 mm / B 160 mm / D 18 mm 
    Gewicht:  489 gr 
    Seiten:  212 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    This book offers a unique new look at the familiar quantification theory from the point of view of mathematical symmetry and spatial symmetry. Symmetry exists in many aspects of our life¿for instance, in the arts and biology as an ingredient of beauty and equilibrium, and more importantly, for data analysis as an indispensable representation of functional optimality. This unique focus on symmetry clarifies the objectives of quantification theory and the demarcation of quantification space, something that has never caught the attention of researchers. Mathematical symmetry is well known, as can be inferred from Hirschfeld¿s simultaneous linear regressions, but spatial symmetry has not been discussed before, except for what one may infer from Nishisatös dual scaling. The focus on symmetry here clarifies the demarcation of quantification analysis and makes it easier to understand such a perennial problem as that of joint graphical display in quantification theory. The new framework will help advance the frontier of further developments of quantification theory. Many numerical examples are included to clarify the details of quantification theory, with a focus on symmetry as its operational principle. In this way, the book is useful not only for graduate students but also for researchers in diverse areas of data analysis.

      



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