<?xml version="1.0" encoding="UTF-8"?>
<resource xmlns="http://datacite.org/schema/kernel-4" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://datacite.org/schema/kernel-4 http://schema.datacite.org/meta/kernel-4.1/metadata.xsd">
  <identifier identifierType="DOI">10.18453/rosdok_id00005109</identifier>
  <creators>
    <creator>
      <creatorName nameType="Personal">Beese, Martina</creatorName>
      <givenName>Martina</givenName>
      <familyName>Beese</familyName>
      <nameIdentifier nameIdentifierScheme="GND" schemeURI="http://d-nb.info/gnd/">http://d-nb.info/gnd/138990959X</nameIdentifier>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="https://orcid.org/">https://orcid.org/0009-0001-2849-5960</nameIdentifier>
    </creator>
  </creators>
  <titles>
    <title>Analysis of incomplete data sets in numerical chemometrics</title>
  </titles>
  <publisher>Universität Rostock</publisher>
  <publicationYear>2024</publicationYear>
  <resourceType resourceTypeGeneral="Text" />
  <subjects>
    <subject xml:lang="en" schemeURI="http://dewey.info/" subjectScheme="dewey">510 Mathematics</subject>
  </subjects>
  <dates>
    <date dateType="Created">2024</date>
  </dates>
  <language>en</language>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="PURL">https://purl.uni-rostock.de/rosdok/id00005109</alternateIdentifier>
    <alternateIdentifier alternateIdentifierType="URN">urn:nbn:de:gbv:28-rosdok_id00005109-5</alternateIdentifier>
  </alternateIdentifiers>
  <descriptions>
    <description descriptionType="Abstract">The nonnegative matrix factorization (NMF) problem does not have a unique solution. A low-dimensional representation can be used to determine the set of solutions. However, the matrix to be factorized may be incomplete, making the common approaches to determine the set of solutions only applicable to the largest complete submatrix. This thesis shows a way to approximate the set of solutions of the NMF problem for incomplete matrices with maximum utilization of the given information. This is done using approaches from cone theory, which allow to represent the given incomplete matrix.</description>
  </descriptions>
</resource>
