MULTINOMIAL RESPONSE REGRESSION MODELS AND DIAGNOSTIC METHODS

DOI 2 Citations
  • Ochi Yoshimichi
    Department of Computer Science and Intelligent Systems, Oita University
  • Kishino Kiyohiro
    Department of Information Science and Systems Engineering, Graduate School of Engineering, Oita University:(Present address)Suzuki Co.
  • Uesugi Hiromoto
    Department of Information Science and Systems Engineering, Graduate School of Engineering, Oita University:(Present address)ENICOM
  • Obata Tsuneshi
    Department of Computer Science and Intelligent Systems, Oita University

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Other Title
  • 多項反応における回帰分析と診断法

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Description

Diagnostic methods for multinomial response regression methods are developed as an extension of the regression diagnostic procedure introduced by Pregibon for the case of the binomial logistic regression. For multinomial responses, there exist various indices of association, such as multinomial logit, cumulative logit, adjacent logit, and so on, according to the nominal or ordinal nature of the responses and concepts of the ordering. Regression models are used to reveal the relations of a designated index and possible explanatory variables. We develop diagnostic tools for these regression problems of moderately wide range and evaluate their usefulness and limitations via the applications of the diagnostics for the analyses of a few published data sets.

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Details 詳細情報について

  • CRID
    1390001204384451200
  • NII Article ID
    110001239593
  • DOI
    10.20551/jscswabun.7.2_111
  • ISSN
    21899789
    09148930
  • Text Lang
    ja
  • Data Source
    • JaLC
    • CiNii Articles
  • Abstract License Flag
    Disallowed

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