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Edgeworth-type expansion of the density of the classifier when growth curves are classified via likelihood
Linköping University, Department of Mathematics, Applied Mathematics. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-5559-4120
Linköping University, Department of Mathematics, Applied Mathematics. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Mathematics, Applied Mathematics. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0001-9896-4438
2023 (English)Report (Other academic)
Abstract [en]

In this paper, probabilities of misclassification of a two-step likelihood-based discriminant rule are established for the classification of growth curves. The defined two-step classifier considers the fact that the growth curves might not belong to any of the two predetermined populations. The distribution for the classifier is approximated via an Edgeworth-type expansion.
Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2023. , p. 15
Series
LiTH-MAT-R, ISSN 0348-2960 ; 2023/02
Keywords [en]
Edgeworth-type expansion, Growth Curve model; Likelihood-based classification; Misclassifications errors
National Category
Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:liu:diva-193575ISRN: LiTH-MAT-R-2023/02DOI: 10.3384/LiTH-MAT-R-2023-02OAI: oai:DiVA.org:liu-193575DiVA, id: diva2:1755294
Available from: 2023-05-08 Created: 2023-05-08 Last updated: 2023-08-22Bibliographically approved

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Umunoza Gasana, Emelynevon Rosen, DietrichSingull, Martin

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Umunoza Gasana, Emelynevon Rosen, DietrichSingull, Martin
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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
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