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Comparing Multivariate Regression Methods For Compositional Data: Through Simulation Studies & Applications
Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
2017 (English)Independent thesis Basic level (degree of Bachelor), 180 HE creditsStudent thesis
Abstract [en]

Compositional data, where measurements are vectors with each component constituting a percentage of a whole, is abundant throughout many disciplines of science. Consequently, there is a strong need to establish valid statistical procedures for this type of data. In this work the basic theory of the compositional sample space is presented and through simulation studies and a case study on data from industrial applications, the current available methods for regression as applied to compositional data are evaluated. The main focus of this work is to establish linear regression in a way compatible with compositional data sets and compare this approach with the alternative of applying standard multivariate regression methods on raw compositional data. It is found that for several data sets, the difference between 'naive' multivariate linear regression and compositional linear regression is negligible; while for others (in particular where the dependence of covariates is not strictly linear) the compositional regression methods are shown to be stronger.

Place, publisher, year, edition, pages
2017. , p. 38
Keywords [en]
Compositional Data, Regression
National Category
Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:umu:diva-138463OAI: oai:DiVA.org:umu-138463DiVA, id: diva2:1135466
Educational program
Bachelor of Science in Physics and Applied Mathematics
Presentation
2017-08-18, 12:24 (English)
Supervisors
Examiners
Available from: 2017-09-13 Created: 2017-08-23 Last updated: 2017-09-13Bibliographically approved

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fulltext(1662 kB)151 downloads
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Department of Mathematics and Mathematical Statistics
Probability Theory and Statistics

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • 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