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Misclassification Probabilities through Edgeworth-type Expansion for the Distribution of the Maximum Likelihood based Discriminant Function

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اقرأ أكثر حفظ في قائمتي
  • المؤلفون: Umunoza Gasana, Emelyne
  • نوع التسجيلة:
    Electronic Resource
  • الدخول الالكتروني :
    http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-175873
    Linköping Studies in Science and Technology. Licentiate Thesis, 0280-7971 ; 1911
  • معلومة اضافية
    • Publisher Information:
      Linköpings universitet, Tillämpad matematik Linköpings universitet, Tekniska fakulteten Linköping, Sweden 2021
    • نبذة مختصرة :
      This thesis covers misclassification probabilities via an Edgeworth-type expansion of the maximum likelihood based discriminant function. When deriving misclassification errors, first the expectation and variance in the population are assumed to be known where the variance is the same across populations and thereafter we consider the case where those parameters are unknown. Cumulants of the discriminant function for discriminating between two multivariate normal populations are derived. Approximate probabilities of the misclassification errors are established via an Edgeworth-type expansion using a standard normal distribution.
    • الموضوع:
      Cumulants of discriminant function; Edgeworth-type expansion; Linear discriminant analysis; Misclassification errors; Probability Theory and Statistics; Sannolikhetsteori och statistik; Licentiate thesis, monograph; info:eu-repo/semantics/masterThesis; text
    • الرقم المعرف:
      10.3384.lic.diva-175873
    • Availability:
      Open access content. Open access content
      info:eu-repo/semantics/openAccess
    • Note:
      application/pdf
      English
    • Other Numbers:
      UPE oai:DiVA.org:liu-175873
      urn:isbn:9789179296193
      doi:10.3384/lic.diva-175873
      1280647427
    • Contributing Source:
      UPPSALA UNIV LIBR
      From OAIster®, provided by the OCLC Cooperative.
    • الرقم المعرف:
      edsoai.on1280647427
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