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<!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.0 20120330//EN" "JATS-journalpublishing1.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" article-type="research-article"><front><journal-meta><journal-id journal-id-type="publisher-id">INFORMATICA</journal-id><journal-title-group><journal-title>Informatica</journal-title></journal-title-group><issn pub-type="epub">0868-4952</issn><issn pub-type="ppub">0868-4952</issn><publisher><publisher-name>VU</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="publisher-id">INF3108</article-id><article-id pub-id-type="doi">10.3233/INF-1992-3108</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research article</subject></subj-group></article-categories><title-group><article-title>Model order determination using robust hypothesis-testing procedures</article-title></title-group><contrib-group><contrib contrib-type="Author"><name><surname>Pupeikis</surname><given-names>Rimantas</given-names></name><xref ref-type="aff" rid="j_INFORMATICA_aff_000"/></contrib><aff id="j_INFORMATICA_aff_000">Institute of Mathematics and Informatics, Lithuanian Academy of Sciences, 2600 Vilnius, Akademijos St.4, Lithuania</aff></contrib-group><pub-date pub-type="epub"><day>01</day><month>01</month><year>1992</year></pub-date><volume>3</volume><issue>1</issue><fpage>88</fpage><lpage>97</lpage><abstract><p>In the previous paper (Pupeikis, 1990) the problem of model order determination in the presence of outliers in observations has been considered by means of introducing robust analogues of the sample covariance and cross-covariance functions instead of the respective classical function meanings used in the determinant ratio test. The aim of the given paper is the development of statistical hypothesis-testing procedures for determination of the model order of dynamic objects, described by linear difference equations. The results of numerical simulations by computer (Table 1) show the efficiency of the proposed statistical procedures for determining the model order by input-output data in the presence of outliers in observations.</p></abstract><kwd-group><label>Keywords</label><kwd>model order</kwd><kwd>outlier</kwd><kwd>robustness</kwd><kwd>robust inference</kwd></kwd-group></article-meta></front></article>